Notebooks/12_SPARQL.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction to Databases\n",
    "\n",
    "### Using SPARQL\n",
    "\n",
    "Based on [this](https://rebeccabilbro.github.io/sparql-from-python/), [this](https://www.wikidata.org/wiki/Wikidata:SPARQL_tutorial) and [this](https://towardsdatascience.com/where-do-mayors-come-from-querying-wikidata-with-python-and-sparql-91f3c0af22e2) blog posts  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import time\n",
    "import json\n",
    "import datetime\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import requests\n",
    "import matplotlib.pyplot as plt\n",
    "from datetime import datetime\n",
    "\n",
    "from SPARQLWrapper import SPARQLWrapper, JSON\n",
    "\n",
    "%matplotlib inline\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introducing SPARQL\n",
    "\n",
    "[SPARQL](https://en.wikipedia.org/wiki/SPARQL) is a query language used to retrieve data stored as [RDF](https://en.wikipedia.org/wiki/Resource_Description_Framework) (Resource Description Framework) and it is standardized by the W3C. The syntax is similar to SQL, but it has some differences for people trained in SQL. One key difference is that in SQL you tend to avoid `JOIN` clauses as they can slow down queries, but in SPARQL the queries mostly consist of joins.\n",
    "\n",
    "RDF represents data in the format [Subject - Predicate - Object](https://en.wikipedia.org/wiki/Semantic_triple)\n",
    "\n",
    "SPARQL contains capabilities for querying required and optional graph patterns along with their conjunctions and disjunctions.  \n",
    "SPARQL also supports extensible value testing and constraining queries by source RDF graph.  \n",
    "The results of SPARQL queries can be results sets or RDF graphs.\n",
    "\n",
    "SPARQL allows us to express queries as three-part statements:\n",
    "\n",
    "\n",
    "> PREFIX ... // identifies & nicknames namespace URIs of desired variables  \n",
    "> SELECT ... // lists variables to be returned (start with a ?)  \n",
    "> WHERE  ... // contains restrictions on variables expressed as triples  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SPARQL basics:  \n",
    "\n",
    "A simple SPARQL query looks like this: \n",
    "\n",
    "```sparql\n",
    "SELECT ?a ?b ?c  \n",
    "WHERE  \n",
    "{  \n",
    "  x y ?a.  \n",
    "  m n ?b.  \n",
    "  ?b f ?c.  \n",
    "}  \n",
    "```\n",
    "\n",
    "The SELECT clause lists variables that you want returned (variables start with a question mark), and the WHERE clause contains restrictions on them, mostly in the form of triples. A triple can be read like a sentence (which is why it ends with a period), with a subject, a predicate, and an object:   \n",
    "\n",
    "```sparql\n",
    "SELECT ?fruit  \n",
    "WHERE  \n",
    "{  \n",
    "  ?fruit color yellow.  \n",
    "  ?fruit taste sour.  \n",
    "}\n",
    "```\n",
    "\n",
    "Given that color and taste are properties in some triples "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### First Example: Query DBPedia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Specify the DBPedia endpoint\n",
    "sparql = SPARQLWrapper(\"http://dbpedia.org/sparql\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Query for the description of \"Capsaicin\", filtered by language\n",
    "\n",
    "sparql.setQuery(\n",
    "    \"\"\"\n",
    "    PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>\n",
    "    SELECT ?comment\n",
    "    WHERE { <http://dbpedia.org/resource/Capsaicin> rdfs:comment ?comment\n",
    "    FILTER (LANG(?comment)='en')\n",
    "    } \n",
    "    \"\"\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert results to JSON format\n",
    "sparql.setReturnFormat(JSON)\n",
    "result = sparql.query().convert()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['head', 'results'])\n"
     ]
    }
   ],
   "source": [
    "# The return data contains \"bindings\" (a list of dictionaries)\n",
    "print(result.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'head': {'link': [], 'vars': ['comment']},\n",
       " 'results': {'distinct': False,\n",
       "  'ordered': True,\n",
       "  'bindings': [{'comment': {'type': 'literal',\n",
       "     'xml:lang': 'en',\n",
       "     'value': 'Capsaicin (/kæpˈseɪ.ᵻsɪn/ (INN); 8-methyl-N-vanillyl-6-nonenamide) is an active component of chili peppers, which are plants belonging to the genus Capsicum. It is an irritant for mammals, including humans, and produces a sensation of burning in any tissue with which it comes into contact. Capsaicin and several related compounds are called capsaicinoids and are produced as secondary metabolites by chili peppers, probably as deterrents against certain mammals and fungi. Pure capsaicin is a volatile, hydrophobic, colorless, odorless, crystalline to waxy compound.'}}]}}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Capsaicin (/kæpˈseɪ.ᵻsɪn/ (INN); 8-methyl-N-vanillyl-6-nonenamide) is an active component of chili peppers, which are plants belonging to the genus Capsicum. It is an irritant for mammals, including humans, and produces a sensation of burning in any tissue with which it comes into contact. Capsaicin and several related compounds are called capsaicinoids and are produced as secondary metabolites by chili peppers, probably as deterrents against certain mammals and fungi. Pure capsaicin is a volatile, hydrophobic, colorless, odorless, crystalline to waxy compound.\n"
     ]
    }
   ],
   "source": [
    "for hit in result[\"results\"][\"bindings\"]:\n",
    "    # We want the \"value\" attribute of the \"comment\" field\n",
    "    print(hit[\"comment\"][\"value\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Second Example: Querying Wikidata\n",
    "\n",
    "Based mainly on [this excellent blog post](https://towardsdatascience.com/where-do-mayors-come-from-querying-wikidata-with-python-and-sparql-91f3c0af22e2) with [code available here](https://github.com/njanakiev/wikidata-mayors). Also based on [this tutorial](https://www.wikidata.org/wiki/Wikidata:SPARQL_tutorial)  \n",
    "\n",
    "[Wikidata](https://www.wikidata.org/) is a free and collaborative [Linked Open Data (LOD)](https://en.wikipedia.org/wiki/Linked_data) knowledge base which can be edited by humans and machines. It contains millions of statements, such as “the capital of Canada is Ottawa”, or “the Mona Lisa is painted in oil paint on poplar wood”, or “gold has a melting point of 1,064.18 degrees Celsius”.  \n",
    "The project started 2012 by the [Wikimedia Foundation](https://foundation.wikimedia.org/wiki/Home) as an effort to centralize interwiki links, infoboxes and enable rich queries. Its ambitious goal is to structure the whole human knowledge in a way that is machine readable and it speaks well to the vision of Tim Berners-Lee in his [TED talk](https://www.youtube.com/watch?v=OM6XIICm_qo) of 2009. Surprisingly, the idea of the [Semantic Web](https://en.wikipedia.org/wiki/Semantic_Web) existed already in 2001 which is comprised of Linked Data. There have been many projects preceding Wikidata. There is [DBpedia](https://en.wikipedia.org/wiki/DBpedia) which is based on the infoboxes in Wikipedia, [Friend of a Friend (FOAF)](https://en.wikipedia.org/wiki/FOAF_(ontology)) which is an ontology to describe relationships in social networks, [GeoNames](https://en.wikipedia.org/wiki/GeoNames) which provides a database with geographical names, [Upper Mapping and Binding Exchange Layer (UMBEL)](https://en.wikipedia.org/wiki/UMBEL) which is a knowledge graph of concepts and entities and a whole set of others, but Wikidata seems to be the most ambitious project between them.\n",
    "\n",
    "All of the data there is free (under the [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/) aka public domain), while anyone can edit and contribute to it. So it works in a similar way to Wikipedia. On most (if not all) Wikipedia pages, there is a _Wikidata Item_ link to its corresponding item in Wikidata, where you can find the linked information listed. Note that you can still find holes, but as it is a community effort, this is becoming better and growing over time by every contribution. To access the structured data you can query Wikidata by using its [SPARQL endpoint](https://query.wikidata.org/) which enables you to run advanced queries, or by using its [REST API](https://www.wikidata.org/w/api.php).\n",
    "\n",
    "In this diagram, you can see the structure of a Wikidata item. Each item has a list of [statements](https://www.wikidata.org/wiki/Help:Statements), which are triples in the form `SUBJECT` - `PREDICATE` - `OBJECT` (e.g. Douglas Adams is educated at the St John's College). In Wikidata the subject is referred to as [item](https://www.wikidata.org/wiki/Help:Items) and the predicate is referred to as [property](https://www.wikidata.org/wiki/Help:Properties). Each property has a value, which can be again an item, text, number, date, or GPS coordinates among others. Each value can have additional [qualifiers](https://www.wikidata.org/wiki/Help:Qualifiers) which have additional information with other property-value pairs such as start time. This structure will be important when we start to express queries with SPARQL.\n",
    "\n",
    "![Wikidata Data Model](../SampleDBs/wikidata_data_model.png)\n",
    "\n",
    "image from [SPARQL/WIKIDATA Qualifiers, References and Ranks](https://en.wikibooks.org/wiki/SPARQL/WIKIDATA_Qualifiers,_References_and_Ranks).\n",
    "\n",
    "We can use the Wikidata Query Service (WDQS) endpoint to query Wikidata.\n",
    "\n",
    "Let’s say we want to continue our research into spicy things by searching for information about hot sauces in Wikidata. The first step is to find the unique identifier that Wikidata uses to reference “hot sauce”, which we can do by searching on Wikidata. It turns out to be “Q522171”, which is an “entity”, which corresponds to the “wd” prefix in Wikidata.\n",
    "\n",
    "If we want to get back results for all of the kinds of hot sauces cataloged in Wikidata, we want to query for the results that have the direct property – or “wdt” in Wikidata prefix speak – “\n",
    "\n",
    "NOTE: For simple WDQS triples, items should be prefixed with wd:, and properties with wdt:. We don’t need to explicitly alias any prefixes in this case because WDQS already knows many shortcut abbreviations commonly used externally (e.g. rdf, skos, owl, schema, etc.) as well as ones internal to Wikidata, such as:\n",
    "\n",
    "    PREFIX wd: http://www.wikidata.org/entity/\n",
    "    PREFIX wds: http://www.wikidata.org/entity/statement/\n",
    "    PREFIX wdv: http://www.wikidata.org/value/\n",
    "    PREFIX wdt: http://www.wikidata.org/prop/direct/\n",
    "    PREFIX wikibase: http://wikiba.se/ontology#\n",
    "    PREFIX p: http://www.wikidata.org/prop/\n",
    "    PREFIX ps: http://www.wikidata.org/prop/statement/\n",
    "    PREFIX pq: http://www.wikidata.org/prop/qualifier/\n",
    "    PREFIX rdfs: http://www.w3.org/2000/01/rdf-schema#\n",
    "    PREFIX bd: http://www.bigdata.com/rdf#"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "sparql = SPARQLWrapper(\"https://query.wikidata.org/sparql\")\n",
    "\n",
    "# Below we SELECT both the hot sauce items & their labels\n",
    "# in the WHERE clause we specify that we want labels as well as items\n",
    "\n",
    "sparql.setQuery(\"\"\"\n",
    "SELECT ?item ?itemLabel\n",
    "WHERE {?item wdt:P279 wd:Q522171.\n",
    "SERVICE wikibase:label { bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". }\n",
    "}\n",
    "\"\"\")\n",
    "\n",
    "sparql.setReturnFormat(JSON)\n",
    "results = sparql.query().convert()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'head': {'vars': ['item', 'itemLabel']},\n",
       " 'results': {'bindings': [{'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q249114'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'salsa'}},\n",
       "   {'item': {'type': 'uri', 'value': 'http://www.wikidata.org/entity/Q335016'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'Tabasco sauce'}},\n",
       "   {'item': {'type': 'uri', 'value': 'http://www.wikidata.org/entity/Q360459'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Adobo'}},\n",
       "   {'item': {'type': 'uri', 'value': 'http://www.wikidata.org/entity/Q460439'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': \"Blair's 16 Million Reserve\"}},\n",
       "   {'item': {'type': 'uri', 'value': 'http://www.wikidata.org/entity/Q966327'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'harissa'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q1026822'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Chili oil'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q1392674'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'sriracha sauce'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q2227032'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'mojo'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q2279518'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Shito'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q2402909'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Valentina'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q3273096'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'Doubanjiang'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q3474141'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'sauce samouraï'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q3474250'},\n",
       "    'itemLabel': {'type': 'literal', 'value': 'Q3474250'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q4922876'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'nam phrik'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q5104402'},\n",
       "    'itemLabel': {'xml:lang': 'en',\n",
       "     'type': 'literal',\n",
       "     'value': 'Cholula Hot Sauce'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q6961170'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'nam chim'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q7707906'},\n",
       "    'itemLabel': {'xml:lang': 'en', 'type': 'literal', 'value': 'Texas Pete'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q16628511'},\n",
       "    'itemLabel': {'type': 'literal', 'value': 'Q16628511'}},\n",
       "   {'item': {'type': 'uri',\n",
       "     'value': 'http://www.wikidata.org/entity/Q16642516'},\n",
       "    'itemLabel': {'type': 'literal', 'value': 'Q16642516'}}]}}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item.value</th>\n",
       "      <th>itemLabel.value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>http://www.wikidata.org/entity/Q249114</td>\n",
       "      <td>salsa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>http://www.wikidata.org/entity/Q335016</td>\n",
       "      <td>Tabasco sauce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>http://www.wikidata.org/entity/Q360459</td>\n",
       "      <td>Adobo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>http://www.wikidata.org/entity/Q460439</td>\n",
       "      <td>Blair's 16 Million Reserve</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>http://www.wikidata.org/entity/Q966327</td>\n",
       "      <td>harissa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>http://www.wikidata.org/entity/Q1026822</td>\n",
       "      <td>Chili oil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>http://www.wikidata.org/entity/Q1392674</td>\n",
       "      <td>sriracha sauce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>http://www.wikidata.org/entity/Q2227032</td>\n",
       "      <td>mojo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>http://www.wikidata.org/entity/Q2279518</td>\n",
       "      <td>Shito</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>http://www.wikidata.org/entity/Q2402909</td>\n",
       "      <td>Valentina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>http://www.wikidata.org/entity/Q3273096</td>\n",
       "      <td>Doubanjiang</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>http://www.wikidata.org/entity/Q3474141</td>\n",
       "      <td>sauce samouraï</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>http://www.wikidata.org/entity/Q3474250</td>\n",
       "      <td>Q3474250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>http://www.wikidata.org/entity/Q4922876</td>\n",
       "      <td>nam phrik</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>http://www.wikidata.org/entity/Q5104402</td>\n",
       "      <td>Cholula Hot Sauce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>http://www.wikidata.org/entity/Q6961170</td>\n",
       "      <td>nam chim</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>http://www.wikidata.org/entity/Q7707906</td>\n",
       "      <td>Texas Pete</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>http://www.wikidata.org/entity/Q16628511</td>\n",
       "      <td>Q16628511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>http://www.wikidata.org/entity/Q16642516</td>\n",
       "      <td>Q16642516</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  item.value             itemLabel.value\n",
       "0     http://www.wikidata.org/entity/Q249114                       salsa\n",
       "1     http://www.wikidata.org/entity/Q335016               Tabasco sauce\n",
       "2     http://www.wikidata.org/entity/Q360459                       Adobo\n",
       "3     http://www.wikidata.org/entity/Q460439  Blair's 16 Million Reserve\n",
       "4     http://www.wikidata.org/entity/Q966327                     harissa\n",
       "5    http://www.wikidata.org/entity/Q1026822                   Chili oil\n",
       "6    http://www.wikidata.org/entity/Q1392674              sriracha sauce\n",
       "7    http://www.wikidata.org/entity/Q2227032                        mojo\n",
       "8    http://www.wikidata.org/entity/Q2279518                       Shito\n",
       "9    http://www.wikidata.org/entity/Q2402909                   Valentina\n",
       "10   http://www.wikidata.org/entity/Q3273096                 Doubanjiang\n",
       "11   http://www.wikidata.org/entity/Q3474141              sauce samouraï\n",
       "12   http://www.wikidata.org/entity/Q3474250                    Q3474250\n",
       "13   http://www.wikidata.org/entity/Q4922876                   nam phrik\n",
       "14   http://www.wikidata.org/entity/Q5104402           Cholula Hot Sauce\n",
       "15   http://www.wikidata.org/entity/Q6961170                    nam chim\n",
       "16   http://www.wikidata.org/entity/Q7707906                  Texas Pete\n",
       "17  http://www.wikidata.org/entity/Q16628511                   Q16628511\n",
       "18  http://www.wikidata.org/entity/Q16642516                   Q16642516"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_df = pd.json_normalize(results['results']['bindings'])\n",
    "results_df[['item.value', 'itemLabel.value']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ok, this was easy. \n",
    "In this next part, we will build queries for Wikidata with Python and SPARQL by taking a look where mayors in Europe are born. This pipeline was used to obtain data used in this [interactive visualization](https://janakiev.com/wikidata-mayors/), which was done with [deck.gl](http://deck.gl/#/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, we want to list all countries in the European Union.\n",
    "\n",
    "```sparql\n",
    "SELECT ?country ?countryLabel WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n",
    "}\n",
    "```\n",
    "You can try this query yourself [here](https://query.wikidata.org/#SELECT%20%3Fcountry%20%3FcountryLabel%20WHERE%20%7B%0A%20%20%3Fcountry%20wdt%3AP463%20wd%3AQ458.%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20%0A%20%20%20%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%0A%20%20%7D%0A%7D). Note that you can test and play with each query at [https://query.wikidata.org/](https://query.wikidata.org/). The editor there offers a handful of useful features. If you hover over the properties and items in the editor you will get information about them and the editor additionally offers autocompletion. You will also find a list of examples which are quite handy when starting fresh.\n",
    "\n",
    "The statement `?country wdt:P463 wd:Q458.` collects all items which have the property [member of (P463)](https://www.wikidata.org/wiki/Property:P463) with object [European Union (Q458)](https://www.wikidata.org/wiki/Q458) into the variable `country`. As you can see, the statements read like a sentence (i.e. country is a member of the European Union). You also notice that there are the prefixes `wd:` and `wdt:`. These denote items (subjects) with `wd:` and properties (predicates) with `wdt:`. We will cover more complicated prefixes later. \n",
    "\n",
    "Finally, you will see a confusing part `SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }` within the query. This snippet is responsible for retrieving labels for the collected items into an additional variable with `Label` postfix in the specified language (in this case English). In this query, this would be the `countryLabel` variable storing the label for the `country` variable. Note that the label is only retrieved for items that have a label in the particular language selected (in this case `\"en\"` for English), as there might be items that are not translated into this particular language.\n",
    "\n",
    "Interesting sidenote: When running the query you will notice [Kingdom of the Netherlands](https://en.wikipedia.org/wiki/Kingdom_of_the_Netherlands) with Wikidata item [Q29999](https://www.wikidata.org/wiki/Q29999) in the list of European countries. Surprisingly, [Netherlands](https://en.wikipedia.org/wiki/Netherlands) ([Q55](https://www.wikidata.org/wiki/Q55)) is a constituent country of the Kingdom of the Netherlands, but it is not a country. It is similar to how England is part of the United Kingdom. This [video](https://www.youtube.com/watch?v=WBcn-lzTJbk) does a great job explaining the situation if you were puzzled."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Advanced Queries\n",
    "\n",
    "Let's now explore other properties of the countries we have selected. If you take a look at [Germany (Q183)](https://www.wikidata.org/wiki/Q183), then you can see a whole host of properties like [population (P1082)](https://www.wikidata.org/wiki/Property:P1082), [median income (P3529)](https://www.wikidata.org/wiki/Property:P3529) or even images with the [image (P18)](https://www.wikidata.org/wiki/Property:P18) property. SPARQL enables us to retrieve those too which leads us to the next query.\n",
    "\n",
    "```sparql\n",
    "SELECT \n",
    "  ?country ?countryLabel ?population ?area ?medianIncome\n",
    "WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  ?country wdt:P1082 ?population.\n",
    "  ?country wdt:P2046 ?area.\n",
    "  ?country wdt:P3529 ?medianIncome.\n",
    "  \n",
    "  SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n",
    "}\n",
    "```\n",
    "You can try this query [here](https://query.wikidata.org/#SELECT%20%0A%20%20%3Fcountry%20%3FcountryLabel%20%0A%20%20%3Fcapital%20%3FcapitalLabel%0A%20%20%3Fpopulation%20%3Farea%20%3FmedianIncome%0AWHERE%20%7B%0A%20%20%3Fcountry%20wdt%3AP463%20wd%3AQ458.%0A%20%20%3Fcountry%20wdt%3AP36%20%3Fcapital.%0A%20%20%3Fcountry%20wdt%3AP1082%20%3Fpopulation.%0A%20%20%3Fcountry%20wdt%3AP2046%20%3Farea.%0A%20%20%3Fcountry%20wdt%3AP3529%20%3FmedianIncome.%0A%20%20%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22.%20%7D%0A%7D).\n",
    "\n",
    "After trying this query you will notice that the list of countries became shorter.  The reason for this is that each country item that has no population, area or median income as a property is ignored by the query. You can imagine those triples also as a filter constraining the triples that only match this query. We can add the `OPTIONAL` clause which will leave those variables empty if the query cannot find triples within this clause.\n",
    "\n",
    "```sparql\n",
    "SELECT \n",
    "  ?country ?countryLabel ?population ?area ?medianIncome\n",
    "WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  OPTIONAL { ?country wdt:P1082 ?population }\n",
    "  OPTIONAL { ?country wdt:P2046 ?area }\n",
    "  OPTIONAL { ?country wdt:P3529 ?medianIncome }\n",
    "    \n",
    "  SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n",
    "}\n",
    "```\n",
    "\n",
    "You can try this query [here](https://query.wikidata.org/#SELECT%20%0A%20%20%3Fcountry%20%3FcountryLabel%20%0A%20%20%3Fcapital%20%3FcapitalLabel%0A%20%20%3Fpopulation%20%3Farea%20%3FmedianIncome%0AWHERE%20%7B%0A%20%20%3Fcountry%20wdt%3AP463%20wd%3AQ458.%0A%20%20%3Fcountry%20wdt%3AP36%20%3Fcapital.%0A%20%20%20%20%0A%20%20OPTIONAL%20%7B%20%3Fcountry%20wdt%3AP1082%20%3Fpopulation%20%7D%0A%20%20OPTIONAL%20%7B%20%3Fcountry%20wdt%3AP2046%20%3Farea%20%7D%0A%20%20OPTIONAL%20%7B%20%3Fcountry%20wdt%3AP3529%20%3FmedianIncome%20%7D%0A%20%20%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20bd%3AserviceParam%20wikibase%3Alanguage%20%22en%22.%20%7D%0A%7D). Now we see in the table that we will find all countries again.\n",
    "\n",
    "![Query Result](../SampleDBs/query_result.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SPARQL Data Representation\n",
    "\n",
    "We continue our journey with a complicated query which we will unpack step by step. Our goal is now to get for all countries, the capital, the population, the mayor, his birthday and finally his birthplace. The query looks like this.\n",
    "\n",
    "```sparql\n",
    "SELECT DISTINCT \n",
    "  ?country ?countryLabel ?capital ?capitalLabel ?population \n",
    "  ?mayor ?mayorLabel ?birth_place ?birth_placeLabel ?birth_date ?age\n",
    "WHERE {\n",
    "  # Get all european countries, their capitals and the population of the capital\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  ?country wdt:P36 ?capital.\n",
    "  OPTIONAL { ?capital wdt:P1082 ?population. }\n",
    "  \n",
    "  # Get all mayors without an end date\n",
    "  ?capital p:P6 ?statement.\n",
    "  ?statement ps:P6 ?mayor.\n",
    "  FILTER NOT EXISTS { ?statement pq:P582 ?end_date }\n",
    "  \n",
    "  # Get birth place, birth date and age of mayor\n",
    "  ?mayor wdt:P19 ?birth_place.\n",
    "  ?mayor wdt:P569 ?birth_date.\n",
    "  BIND(year(now()) - year(?birth_date) AS ?age)\n",
    "  \n",
    "  SERVICE wikibase:label { \n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "```\n",
    "You can try this query [here](https://query.wikidata.org/#SELECT%20DISTINCT%20%0A%20%20%3Fcountry%20%3FcountryLabel%20%3Fcapital%20%3FcapitalLabel%20%3Fpopulation%20%0A%20%20%3Fmayor%20%3FmayorLabel%20%3Fbirth_place%20%3Fbirth_placeLabel%20%3Fbirth_date%20%3Fage%0AWHERE%20%7B%0A%20%20%3Fcountry%20wdt%3AP463%20wd%3AQ458.%0A%20%20%3Fcountry%20wdt%3AP36%20%3Fcapital.%0A%20%20OPTIONAL%20%7B%20%3Fcapital%20wdt%3AP1082%20%3Fpopulation.%20%7D%0A%20%20%0A%20%20%3Fcapital%20p%3AP6%20%3Fstatement.%0A%20%20%3Fstatement%20ps%3AP6%20%3Fmayor.%0A%20%20FILTER%20NOT%20EXISTS%20%7B%20%3Fstatement%20pq%3AP582%20%3Fend_date%20%7D%0A%20%20%20%20%0A%20%20%3Fmayor%20wdt%3AP19%20%3Fbirth_place.%0A%20%20%3Fmayor%20wdt%3AP569%20%3Fbirth_date.%0A%20%20BIND%28year%28now%28%29%29%20-%20year%28%3Fbirth_date%29%20AS%20%3Fage%29%0A%20%20%0A%20%20SERVICE%20wikibase%3Alabel%20%7B%20%0A%20%20%20%20bd%3AserviceParam%20wikibase%3Alanguage%20%22%5BAUTO_LANGUAGE%5D%2Cen%22.%20%0A%20%20%7D%0A%7D).\n",
    "\n",
    "Let's unpack what is happening here. First, we start by getting the capital of the country which we simply get via the [capital (P36)](https://www.wikidata.org/wiki/Property:P36) property. Next, we get to a more complicated part. To understand how to get to the mayor we have to look at the SPARQL Data Representation in this diagram.\n",
    "\n",
    "![SPARQL data representation](../SampleDBs/SPARQL_data_representation.png)\n",
    "\n",
    "image from [SPARQL/WIKIDATA Qualifiers, References and Ranks](https://en.wikibooks.org/wiki/SPARQL/WIKIDATA_Qualifiers,_References_and_Ranks).\n",
    "\n",
    "This graph of the data representation that you see here shows the ways you can traverse it to get to various pieces of information with SPARQL starting from an item (in the graph shown as `wd:Q1234`). You can see on the left the classical path we took in our previous triples by using the `wdt:` prefix which leads to the value which can be another item, a numeric value (e.g. the population as in one of the previous queries) or various other data types.\n",
    "\n",
    "If you take a look at an item like [Rome (Q220)](https://www.wikidata.org/wiki/Q220), you will notice that there are various statements for the [head of government (P6)](https://www.wikidata.org/wiki/Property:P6). We want to get the one which has no end date. We can do this by traversing to the statement node with the `p:` prefix and storing it in the `statement` variable. From this variable, we can get the mayor with the `ps:` prefix. We could have done that with `wdt:` as we already have learned but we want to go one step further. We want to get to [end time (P582)](https://www.wikidata.org/wiki/Property:P582) which is stored as a qualifier in the statement. We can traverse to the qualifier with the `pq:` prefix which would give us the end date, but we want mayors without an end date. This can be done by using the `FILTER NOT EXISTS` clause which excludes all triples with statement node that have an end date.\n",
    "\n",
    "In the final part, we collect the birthplace, the birth date and the age of the mayor. In order to calculate his age, we use the `BIND` expression. This expression can be used to bind some expression to a variable (in our case the age variable). For this expression, we subtract the year of the birth date with the current year. This concludes this query. You can dig deeper in [SPARQL/WIKIDATA Qualifiers, References and Ranks](https://en.wikibooks.org/wiki/SPARQL/WIKIDATA_Qualifiers,_References_and_Ranks) which describes the data representation in further detail."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have seen how to work with SPARQL and we can also download the resulting tables in the editor, but how do we will automate the whole processwith Python, which enables us to directly load and analyze the data we have queried. To do this, we will employ the [request](http://docs.python-requests.org/en/master/) module which does a great job at doing HTTP requests with all its necessary tooling. We can create the request by adding the query as a parameter as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://query.wikidata.org/sparql'\n",
    "\n",
    "query = \"\"\"\n",
    "SELECT \n",
    "  ?countryLabel ?population ?area ?medianIncome ?age\n",
    "WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  OPTIONAL { ?country wdt:P1082 ?population }\n",
    "  OPTIONAL { ?country wdt:P2046 ?area }\n",
    "  OPTIONAL { ?country wdt:P3529 ?medianIncome }\n",
    "  OPTIONAL { ?country wdt:P571 ?inception. \n",
    "    BIND(year(now()) - year(?inception) AS ?age)\n",
    "  }\n",
    "  SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n",
    "}\n",
    "\"\"\"\n",
    "r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "data = r.json()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have packed the query in the `query` variable and we need to additionally supply request with the SPARQL endpoint URL which is [https://query.wikidata.org/sparql](https://query.wikidata.org/sparql). We want to use JSON as an output file, so we add this also to our request. The API returns XML as default but supports besides JSON also TSV, CSV and Binary RDF. This request returns a JSON with all the rows collected from the query, which we can use collect the rows into a [Pandas](https://pandas.pydata.org/) DataFrame as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>population</th>\n",
       "      <th>area</th>\n",
       "      <th>medianIncome</th>\n",
       "      <th>age</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Kingdom of Denmark</th>\n",
       "      <td>5930987.0</td>\n",
       "      <td>2220930.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1220.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kingdom of the Netherlands</th>\n",
       "      <td>17100715.0</td>\n",
       "      <td>42201.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>205.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ireland</th>\n",
       "      <td>4761865.0</td>\n",
       "      <td>70273.0</td>\n",
       "      <td>25969.0</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belgium</th>\n",
       "      <td>11431406.0</td>\n",
       "      <td>30528.0</td>\n",
       "      <td>31112.0</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hungary</th>\n",
       "      <td>9769526.0</td>\n",
       "      <td>93011.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1020.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            population       area  medianIncome     age\n",
       "country                                                                \n",
       "Kingdom of Denmark           5930987.0  2220930.0           NaN  1220.0\n",
       "Kingdom of the Netherlands  17100715.0    42201.0           NaN   205.0\n",
       "Ireland                      4761865.0    70273.0       25969.0    83.0\n",
       "Belgium                     11431406.0    30528.0       31112.0   190.0\n",
       "Hungary                      9769526.0    93011.4           NaN  1020.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from collections import OrderedDict\n",
    "\n",
    "countries = []\n",
    "for item in data['results']['bindings']:\n",
    "    countries.append(OrderedDict({\n",
    "        'country': item['countryLabel']['value'],\n",
    "        'population': item['population']['value'],\n",
    "        'area': item['area']['value'] \n",
    "            if 'area' in item else None,\n",
    "        'medianIncome': item['medianIncome']['value'] \n",
    "            if 'medianIncome' in item else None,\n",
    "        'age': item['age']['value'] \n",
    "            if 'age' in item else None}))\n",
    "\n",
    "df = pd.DataFrame(countries)\n",
    "df.set_index('country', inplace=True)\n",
    "df = df.astype({'population': float, 'area': float, 'medianIncome': float, 'age': float})\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's explore the collected data visually and compare the various properties for each country. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "\n",
    "plt.figure(figsize=(16, 12))\n",
    "for i, label in enumerate(['population', 'medianIncome', 'area', 'age']):\n",
    "    plt.subplot(2, 2, i + 1)\n",
    "    df_plot = df[label].sort_values().dropna()\n",
    "    df_plot.plot(kind='barh', color='C0', ax=plt.gca());\n",
    "    plt.ylabel('')\n",
    "    plt.xticks(rotation=30)\n",
    "    plt.title(label.capitalize())\n",
    "    plt.ticklabel_format(style='plain', axis='x')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mayors of all European Capitals\n",
    "\n",
    "In our final query, we will take a look at where mayors are born by adding the coordinates to the query. In order to get the latitude and longitude coordinates as variables, we need to add the following snippet.\n",
    "\n",
    "```sparql\n",
    "?capital p:P625/psv:P625 ?capital_node.\n",
    "?capital_node wikibase:geoLatitude ?capital_lat.\n",
    "?capital_node wikibase:geoLongitude ?capital_lon.\n",
    "```\n",
    "\n",
    "In the first line, we traverse the graph of the previously shown data representation. The slash in `p:P625/psv:P625` means that we continue to the _Value node_ of the [coordinate location (P625)](https://www.wikidata.org/wiki/Property:P625) without using a separate variable for the _Statement node_. Then, `wikibase:geoLatitude` and `wikibase:geoLongitude` are responsible for retrieving the latitude and longitude from the _Value node_ respectively. For more information, take a look at [Precision, Units and Coordinates](https://en.wikibooks.org/wiki/SPARQL/WIKIDATA_Precision,_Units_and_Coordinates)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>countryLabel</th>\n",
       "      <th>capital_lon</th>\n",
       "      <th>capital_lat</th>\n",
       "      <th>population</th>\n",
       "      <th>mayorLabel</th>\n",
       "      <th>birth_date</th>\n",
       "      <th>age</th>\n",
       "      <th>birth_placeLabel</th>\n",
       "      <th>birth_place_lon</th>\n",
       "      <th>birth_place_lat</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>capitalLabel</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bratislava</th>\n",
       "      <td>Slovakia</td>\n",
       "      <td>17.112778</td>\n",
       "      <td>48.144722</td>\n",
       "      <td>429564.0</td>\n",
       "      <td>Matúš Vallo</td>\n",
       "      <td>1977-09-18T00:00:00Z</td>\n",
       "      <td>43.0</td>\n",
       "      <td>Bratislava</td>\n",
       "      <td>17.112778</td>\n",
       "      <td>48.144722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bucharest</th>\n",
       "      <td>Romania</td>\n",
       "      <td>26.083333</td>\n",
       "      <td>44.400000</td>\n",
       "      <td>1883425.0</td>\n",
       "      <td>Nicușor Dan</td>\n",
       "      <td>1969-12-20T00:00:00Z</td>\n",
       "      <td>51.0</td>\n",
       "      <td>Făgăraș</td>\n",
       "      <td>24.971389</td>\n",
       "      <td>45.842222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Amsterdam</th>\n",
       "      <td>Kingdom of the Netherlands</td>\n",
       "      <td>4.900000</td>\n",
       "      <td>52.383333</td>\n",
       "      <td>860124.0</td>\n",
       "      <td>Femke Halsema</td>\n",
       "      <td>1966-04-25T00:00:00Z</td>\n",
       "      <td>54.0</td>\n",
       "      <td>Haarlem</td>\n",
       "      <td>4.640556</td>\n",
       "      <td>52.380278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Madrid</th>\n",
       "      <td>Spain</td>\n",
       "      <td>-3.691944</td>\n",
       "      <td>40.418889</td>\n",
       "      <td>3266126.0</td>\n",
       "      <td>José Luis Martínez-Almeida</td>\n",
       "      <td>1975-04-17T00:00:00Z</td>\n",
       "      <td>45.0</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>-3.691944</td>\n",
       "      <td>40.418889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Valletta</th>\n",
       "      <td>Malta</td>\n",
       "      <td>14.512500</td>\n",
       "      <td>35.897778</td>\n",
       "      <td>6444.0</td>\n",
       "      <td>Alexiei Dingli</td>\n",
       "      <td>1979-12-29T00:00:00Z</td>\n",
       "      <td>41.0</td>\n",
       "      <td>Valletta</td>\n",
       "      <td>14.512500</td>\n",
       "      <td>35.897778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            countryLabel  capital_lon  capital_lat  \\\n",
       "capitalLabel                                                         \n",
       "Bratislava                      Slovakia    17.112778    48.144722   \n",
       "Bucharest                        Romania    26.083333    44.400000   \n",
       "Amsterdam     Kingdom of the Netherlands     4.900000    52.383333   \n",
       "Madrid                             Spain    -3.691944    40.418889   \n",
       "Valletta                           Malta    14.512500    35.897778   \n",
       "\n",
       "              population                  mayorLabel            birth_date  \\\n",
       "capitalLabel                                                                 \n",
       "Bratislava      429564.0                 Matúš Vallo  1977-09-18T00:00:00Z   \n",
       "Bucharest      1883425.0                 Nicușor Dan  1969-12-20T00:00:00Z   \n",
       "Amsterdam       860124.0               Femke Halsema  1966-04-25T00:00:00Z   \n",
       "Madrid         3266126.0  José Luis Martínez-Almeida  1975-04-17T00:00:00Z   \n",
       "Valletta          6444.0              Alexiei Dingli  1979-12-29T00:00:00Z   \n",
       "\n",
       "               age birth_placeLabel  birth_place_lon  birth_place_lat  \n",
       "capitalLabel                                                           \n",
       "Bratislava    43.0       Bratislava        17.112778        48.144722  \n",
       "Bucharest     51.0          Făgăraș        24.971389        45.842222  \n",
       "Amsterdam     54.0          Haarlem         4.640556        52.380278  \n",
       "Madrid        45.0           Madrid        -3.691944        40.418889  \n",
       "Valletta      41.0         Valletta        14.512500        35.897778  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = 'https://query.wikidata.org/sparql'\n",
    "query=\"\"\"\n",
    "SELECT DISTINCT \n",
    "  ?countryLabel ?capitalLabel ?population ?capital_lon ?capital_lat\n",
    "  ?mayorLabel ?birth_date ?age ?birth_place ?birth_placeLabel ?birth_place_lon ?birth_place_lat\n",
    "WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  ?country wdt:P36 ?capital.\n",
    "  OPTIONAL { ?capital wdt:P1082 ?population. }\n",
    "  \n",
    "  # Get latitude longitude coordinates of capital\n",
    "  ?capital p:P625/psv:P625 ?capital_node.\n",
    "  ?capital_node wikibase:geoLatitude ?capital_lat.\n",
    "  ?capital_node wikibase:geoLongitude ?capital_lon.\n",
    "\n",
    "  ?capital p:P6 ?statement.\n",
    "  ?statement ps:P6 ?mayor.\n",
    "  FILTER NOT EXISTS { ?statement pq:P582 ?end_date }\n",
    "\n",
    "  ?mayor wdt:P569 ?birth_date.\n",
    "  BIND(year(now()) - year(?birth_date) AS ?age)\n",
    "  ?mayor wdt:P19 ?birth_place.\n",
    "  ?birth_place wdt:P625 ?birth_place_coordinates.\n",
    "  \n",
    "  # Get latitude longitude coordinates of birth place\n",
    "  ?birth_place p:P625/psv:P625 ?birth_place_node.\n",
    "  ?birth_place_node wikibase:geoLatitude ?birth_place_lat.\n",
    "  ?birth_place_node wikibase:geoLongitude ?birth_place_lon.\n",
    "  \n",
    "  SERVICE wikibase:label { \n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "\"\"\"\n",
    "\n",
    "r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "data = r.json()\n",
    "\n",
    "countries = []\n",
    "for item in data['results']['bindings']:\n",
    "    countries.append(OrderedDict({\n",
    "        label : item[label]['value'] if label in item else None\n",
    "        for label in ['countryLabel', 'capitalLabel',  'capital_lon', 'capital_lat', 'population', \n",
    "                       'mayorLabel', 'birth_date', 'age', \n",
    "                       'birth_placeLabel', 'birth_place_lon', 'birth_place_lat']}))\n",
    "\n",
    "df = pd.DataFrame(countries)\n",
    "df.set_index('capitalLabel', inplace=True)\n",
    "df = df.astype({'population': float, 'age': float,\n",
    "                'capital_lon': float, 'capital_lat': float, \n",
    "                'birth_place_lon': float, 'birth_place_lat': float})\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Taking this data set we can explore the age of the mayors and the population of the capital they are serving."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 5))\n",
    "plt.subplot(1, 2, 1)\n",
    "df['age'].sort_values().plot(kind='barh', color='C0', title='Mayors Age')\n",
    "plt.ylabel('')\n",
    "plt.subplot(1, 2, 2)\n",
    "df['population'].sort_values().plot(kind='barh', color='C0', title='Population')\n",
    "plt.ylabel('')\n",
    "plt.ticklabel_format(style='plain', axis='x')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, let's take a look at how far mayors are born from the capital. For this, we will use the [geopy](https://geopy.readthedocs.io/en/stable/) package to calculate the distance between the coordinates. This [tutorial](https://janakiev.com/blog/gps-points-distance-python/) covers this topic if you are curious why we can't just use euclidean distance on GPS coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from geopy.distance import distance\n",
    "\n",
    "coordinates = df[['capital_lon', 'capital_lat', 'birth_place_lon', 'birth_place_lat']]\n",
    "df['distance'] = [distance((lat0, lon0), (lat1, lon1)).m \n",
    "                for lon0, lat0, lon1, lat1 in coordinates.values]\n",
    "\n",
    "df['distance'].sort_values().plot(kind='barh', color='C0', logx=True, figsize=(12, 7))\n",
    "plt.xlabel('Distance (m)')\n",
    "plt.ylabel('');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we can see that most mayors tend to be born in or close to the city where they later serve (note, that the chart is in log-scale). We can see that Athens leads the exceptions with their current mayor (Giorgos Kaminis) born in New York, USA and Paris with their current mayor (Anne Hidalgo) born in San Fernando, Spain. From there the distances drop significantly.\n",
    "\n",
    "Now we will get a list of all mayors in Europe, with the script from [this source](https://github.com/njanakiev/wikidata-mayors/blob/master/load_european_mayors.py), which deals with exceptions (like mayors born in countries that do not exist anymore) and the queries need to be done for each country separately because there is a limit on the queries.  \n",
    "\n",
    "First we want to select all [members](https://www.wikidata.org/wiki/Property:P463) the [European Union](https://www.wikidata.org/wiki/Q458) and the [European Free Trade Association](https://www.wikidata.org/wiki/Q166546). As before, we will use the [Wikipedia Query Service](https://query.wikidata.org/) and the [Cats](https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/queries/examples#Cats) example and continue editing from there. Let's start by selecting all countries in Europe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Ireland', 'Hungary', 'Spain', 'Belgium', 'Luxembourg', 'Finland', 'Sweden', 'Denmark', 'Poland', 'Lithuania', 'Italy', 'Austria', 'Greece', 'Portugal', 'Netherlands', 'France', 'United Kingdom', 'Germany', 'Estonia', 'Latvia', 'Czech Republic', 'Slovakia', 'Slovenia', 'Romania', 'Bulgaria', 'Croatia', 'Cyprus', 'Malta', 'Kingdom of the Netherlands', 'Kingdom of Denmark']\n",
      "Length : 30\n"
     ]
    }
   ],
   "source": [
    "url = 'https://query.wikidata.org/sparql'\n",
    "query = \"\"\"\n",
    "SELECT ?country ?countryLabel WHERE {\n",
    "  ?country wdt:P463 wd:Q458.\n",
    "  SERVICE wikibase:label { \n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "\"\"\"\n",
    "r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "data = r.json()\n",
    "\n",
    "country_list = [entry['countryLabel']['value'] for entry in data['results']['bindings']]\n",
    "print(country_list)\n",
    "print('Length :', len(country_list))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we want to apply a [`UNION`](https://en.wikibooks.org/wiki/SPARQL/UNION) to get countries from both the European Union and European Free Trade Association. Additionally we want to remove doubles that occur through the union, by using the `DISTINCT` modifier before `SELECT`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Kingdom of Denmark', 'Belgium', 'Portugal', 'Germany', 'Malta', 'Romania', 'Finland', 'Estonia', 'Austria', 'Switzerland', 'Spain', 'Italy', 'Bulgaria', 'Ireland', 'Netherlands', 'France', 'Sweden', 'Denmark', 'Greece', 'Czech Republic', 'Hungary', 'Norway', 'Poland', 'Slovakia', 'United Kingdom', 'Slovenia', 'Cyprus', 'Lithuania', 'Latvia', 'Croatia', 'Iceland', 'Luxembourg', 'Liechtenstein', 'Kingdom of the Netherlands']\n",
      "Length : 34\n"
     ]
    }
   ],
   "source": [
    "url = 'https://query.wikidata.org/sparql'\n",
    "query = \"\"\"\n",
    "SELECT DISTINCT ?country ?countryLabel \n",
    "WHERE \n",
    "{\n",
    "  {?country wdt:P463 wd:Q166546} UNION {?country wdt:P463 wd:Q458}\n",
    "  SERVICE wikibase:label { \n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "\"\"\"\n",
    "r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "data = r.json()\n",
    "\n",
    "country_list = [entry['countryLabel']['value'] for entry in data['results']['bindings']]\n",
    "print(country_list)\n",
    "print('Length :', len(country_list))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's define some utility functions to return a Pandas DataFrame with all the columns from the Wikidata query. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def convert_datatype(entry):\n",
    "    if 'datatype' in entry:\n",
    "        if entry['datatype'] == 'http://www.w3.org/2001/XMLSchema#decimal':\n",
    "            return float(entry['value'])\n",
    "        elif entry['datatype'] == 'http://www.w3.org/2001/XMLSchema#integer':    \n",
    "            return int(entry['value'])\n",
    "        elif entry['datatype'] == 'http://www.w3.org/2001/XMLSchema#dateTime':\n",
    "            date = entry['value']\n",
    "            date = None if date.startswith('t') else datetime.strptime(date, '%Y-%m-%dT%H:%M:%SZ')\n",
    "            return date\n",
    "    return entry['value']\n",
    "\n",
    "\n",
    "def wikidata_query(query):\n",
    "    url = 'https://query.wikidata.org/sparql'\n",
    "    try:\n",
    "        r = requests.get(url, params = {'format': 'json', 'query': query})\n",
    "        data = r.json()\n",
    "    except json.JSONDecodeError as e:\n",
    "        raise Exception('Invalid query')\n",
    "    \n",
    "    if ('results' in data) and ('bindings' in data['results']):\n",
    "        columns = data['head']['vars']\n",
    "        rows = []\n",
    "        for binding in data['results']['bindings']:\n",
    "            row = [convert_datatype(binding[col]) if col in binding else None\n",
    "                   for col in columns]\n",
    "            rows.append(row)\n",
    "    else:\n",
    "        raise Exception('No results')\n",
    "    \n",
    "    return pd.DataFrame(rows, columns=columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Query for each Country\n",
    "\n",
    "Let's collect all mayors and their birth cities with Wikidata."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "country_query = \"\"\"\n",
    "SELECT DISTINCT ?country ?countryLabel WHERE {\n",
    "  { ?country wdt:P463 wd:Q166546 } UNION \n",
    "  { ?country wdt:P463 wd:Q458 } UNION \n",
    "  { VALUES ?country { wd:Q55 } }  # Add Netherlands\n",
    "  FILTER( ?country != wd:Q29999 ) # Remove Kingdom of the Netherlands \n",
    "  SERVICE wikibase:label { \n",
    "      bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }\n",
    "}\n",
    "\"\"\"\n",
    "\n",
    "mayor_query = \"\"\"\n",
    "SELECT DISTINCT \n",
    "  ?city ?cityLabel ?city_coordinates ?population \n",
    "  ?mayor ?mayorLabel ?genderLabel ?birth ?age ?start_date ?duration\n",
    "  ?birth_country ?birth_countryLabel \n",
    "  ?birth_city ?birth_cityLabel ?birth_city_coordinates \n",
    "WHERE {{\n",
    "  ?city wdt:P17 wd:{0}.\n",
    "  ?city wdt:P31/wdt:P279* wd:Q515.\n",
    "  ?city p:P6 ?statement.\n",
    "  ?city wdt:P1082 ?population.\n",
    "  ?city wdt:P625 ?city_coordinates.\n",
    "  \n",
    "  ?statement ps:P6 ?mayor.\n",
    "  ?statement pq:P580 ?start_date.\n",
    "  BIND(year(now()) - year(?start_date) AS ?duration)\n",
    "  \n",
    "  OPTIONAL {{ \n",
    "    ?mayor wdt:P569 ?birth. \n",
    "    BIND(year(now()) - year(?birth) AS ?age)\n",
    "  }}\n",
    "  OPTIONAL {{ ?mayor wdt:P21 ?gender. }}\n",
    "  \n",
    "  # Remove all mayors that have an end time\n",
    "  FILTER NOT EXISTS {{ ?statement pq:P582 ?y. }}\n",
    "  # Remove all mayors that are not alive\n",
    "  FILTER NOT EXISTS {{ ?mayor wdt:P570 ?z. }}\n",
    "  \n",
    "  OPTIONAL {{\n",
    "    ?mayor wdt:P19 ?birth_city.\n",
    "    ?birth_city wdt:P625 ?birth_city_coordinates.\n",
    "    ?birth_city wdt:P17 ?birth_country.\n",
    "    \n",
    "    # Remove all historic countries\n",
    "    FILTER NOT EXISTS {{ ?birth_country wdt:P31 wd:Q3024240. }}\n",
    "  }}\n",
    "  \n",
    "  SERVICE wikibase:label {{\n",
    "    bd:serviceParam wikibase:language \"[AUTO_LANGUAGE],en\". \n",
    "  }}\n",
    "}}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Kingdom of Denmark Q756617\n",
      "Entries : 0\n",
      "\n",
      "Belgium Q31\n",
      "Entries : 38\n",
      "\n",
      "Portugal Q45\n",
      "Entries : 2\n",
      "\n",
      "Germany Q183\n",
      "Entries : 237\n",
      "\n",
      "Malta Q233\n",
      "Entries : 0\n",
      "\n",
      "Romania Q218\n",
      "Entries : 260\n",
      "\n",
      "Finland Q33\n",
      "Entries : 10\n",
      "\n",
      "Estonia Q191\n",
      "Entries : 2\n",
      "\n",
      "Austria Q40\n",
      "Entries : 17\n",
      "\n",
      "Switzerland Q39\n",
      "Entries : 18\n",
      "\n",
      "Spain Q29\n",
      "Entries : 56\n",
      "\n",
      "Italy Q38\n",
      "Entries : 27\n",
      "\n",
      "Bulgaria Q219\n",
      "Entries : 8\n",
      "\n",
      "Ireland Q27\n",
      "Entries : 1\n",
      "\n",
      "Netherlands Q55\n",
      "Entries : 24\n",
      "\n",
      "France Q142\n",
      "Entries : 72\n",
      "\n",
      "Sweden Q34\n",
      "Entries : 1\n",
      "\n",
      "Denmark Q35\n",
      "Entries : 10\n",
      "\n",
      "Greece Q41\n",
      "Entries : 6\n",
      "\n",
      "Czech Republic Q213\n",
      "Entries : 107\n",
      "\n",
      "Hungary Q28\n",
      "Entries : 37\n",
      "\n",
      "Norway Q20\n",
      "Entries : 3\n",
      "\n",
      "Poland Q36\n",
      "Entries : 39\n",
      "\n",
      "Slovakia Q214\n",
      "Entries : 6\n",
      "\n",
      "United Kingdom Q145\n",
      "Entries : 11\n",
      "\n",
      "Slovenia Q215\n",
      "Entries : 4\n",
      "\n",
      "Cyprus Q229\n",
      "Entries : 0\n",
      "\n",
      "Lithuania Q37\n",
      "Entries : 5\n",
      "\n",
      "Latvia Q211\n",
      "Entries : 3\n",
      "\n",
      "Croatia Q224\n",
      "Entries : 2\n",
      "\n",
      "Iceland Q189\n",
      "Entries : 2\n",
      "\n",
      "Luxembourg Q32\n",
      "Entries : 5\n",
      "\n",
      "Liechtenstein Q347\n",
      "Entries : 0\n",
      "\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1013 entries, 0 to 4\n",
      "Data columns (total 20 columns):\n",
      " #   Column              Non-Null Count  Dtype         \n",
      "---  ------              --------------  -----         \n",
      " 0   country             1013 non-null   object        \n",
      " 1   city                1013 non-null   object        \n",
      " 2   cityLabel           1013 non-null   object        \n",
      " 3   population          1013 non-null   float64       \n",
      " 4   mayor               1013 non-null   object        \n",
      " 5   mayorLabel          1013 non-null   object        \n",
      " 6   genderLabel         974 non-null    object        \n",
      " 7   birth               730 non-null    datetime64[ns]\n",
      " 8   age                 730 non-null    float64       \n",
      " 9   start_date          1013 non-null   datetime64[ns]\n",
      " 10  duration            1013 non-null   object        \n",
      " 11  birth_country       636 non-null    object        \n",
      " 12  birth_countryLabel  636 non-null    object        \n",
      " 13  birth_city          636 non-null    object        \n",
      " 14  birth_cityLabel     636 non-null    object        \n",
      " 15  city_lon            1013 non-null   float64       \n",
      " 16  city_lat            1013 non-null   float64       \n",
      " 17  birth_city_lon      636 non-null    float64       \n",
      " 18  birth_city_lat      636 non-null    float64       \n",
      " 19  distance            636 non-null    float64       \n",
      "dtypes: datetime64[ns](2), float64(7), object(11)\n",
      "memory usage: 166.2+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "# Get Wikidata code from each country\n",
    "df_countries = wikidata_query(country_query)\n",
    "df_countries['code'] = df_countries['country'].str.split('/').str[-1]\n",
    "\n",
    "# Get mayors for each country\n",
    "df_list = []\n",
    "for index, (country, country_label, country_code) in df_countries.iterrows():\n",
    "    print(country_label, country_code)\n",
    "    df = wikidata_query(mayor_query.format(country_code))\n",
    "    time.sleep(2)  # Avoid hitting maximum queries limit\n",
    "    df.insert(0, 'country', country_label)\n",
    "    print('Entries :', len(df))\n",
    "    print()\n",
    "    \n",
    "    df_list.append(df)\n",
    "\n",
    "# Collect all rows into single table\n",
    "df = pd.concat(df_list)\n",
    "\n",
    "# Convert coordinates lon, lat columns\n",
    "df[['city_lon', 'city_lat']] = df['city_coordinates'].str[6:-1].str.split(' ', expand=True)\n",
    "df[['city_lon', 'city_lat']] = df[['city_lon', 'city_lat']].astype(float)\n",
    "df[['birth_city_lon', 'birth_city_lat']] = df['birth_city_coordinates'].str[6:-1].str.split(' ', expand=True)\n",
    "df[['birth_city_lon', 'birth_city_lat']] = df[['birth_city_lon', 'birth_city_lat']].astype(float)\n",
    "\n",
    "# Calculate distance between city and birth city\n",
    "def calc_distance(row):\n",
    "    lon0, lat0 = row['city_lon'], row['city_lat']\n",
    "    lon1, lat1 = row['birth_city_lon'], row['birth_city_lat']\n",
    "    \n",
    "    if np.isnan(lon1) or np.isnan(lat1):\n",
    "        return None\n",
    "    else:\n",
    "        return distance((lat0, lon0), (lat1, lon1)).m\n",
    "        \n",
    "df['distance'] = df.apply(calc_distance, axis=1)\n",
    "\n",
    "# Drop original coordinates columns\n",
    "df.drop(columns=['city_coordinates', 'birth_city_coordinates'], inplace=True)\n",
    "\n",
    "# Show some information about the table\n",
    "print(df.info())\n",
    "\n",
    "# Save table to file\n",
    "df.to_csv('../SampleDBs/european_mayors.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>city</th>\n",
       "      <th>cityLabel</th>\n",
       "      <th>population</th>\n",
       "      <th>mayor</th>\n",
       "      <th>mayorLabel</th>\n",
       "      <th>genderLabel</th>\n",
       "      <th>birth</th>\n",
       "      <th>age</th>\n",
       "      <th>start_date</th>\n",
       "      <th>duration</th>\n",
       "      <th>birth_country</th>\n",
       "      <th>birth_countryLabel</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_cityLabel</th>\n",
       "      <th>city_lon</th>\n",
       "      <th>city_lat</th>\n",
       "      <th>birth_city_lon</th>\n",
       "      <th>birth_city_lat</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q118958</td>\n",
       "      <td>Leuven</td>\n",
       "      <td>100291.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q2324477</td>\n",
       "      <td>Mohamed Ridouani</td>\n",
       "      <td>male</td>\n",
       "      <td>1979-06-24</td>\n",
       "      <td>41.0</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q118958</td>\n",
       "      <td>Leuven</td>\n",
       "      <td>4.704444</td>\n",
       "      <td>50.877500</td>\n",
       "      <td>4.704444</td>\n",
       "      <td>50.877500</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>120887.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12460</td>\n",
       "      <td>Lier</td>\n",
       "      <td>36646.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1973059</td>\n",
       "      <td>Frank Boogaerts</td>\n",
       "      <td>male</td>\n",
       "      <td>1944-11-16</td>\n",
       "      <td>76.0</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>7</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12460</td>\n",
       "      <td>Lier</td>\n",
       "      <td>4.569722</td>\n",
       "      <td>51.131111</td>\n",
       "      <td>4.569722</td>\n",
       "      <td>51.131111</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1296</td>\n",
       "      <td>Ghent</td>\n",
       "      <td>262219.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12500</td>\n",
       "      <td>Daniël Termont</td>\n",
       "      <td>male</td>\n",
       "      <td>1953-05-19</td>\n",
       "      <td>67.0</td>\n",
       "      <td>2007-01-01</td>\n",
       "      <td>13</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1296</td>\n",
       "      <td>Ghent</td>\n",
       "      <td>3.725278</td>\n",
       "      <td>51.053611</td>\n",
       "      <td>3.725278</td>\n",
       "      <td>51.053611</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12887</td>\n",
       "      <td>Schaerbeek</td>\n",
       "      <td>133010.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q822355</td>\n",
       "      <td>Bernard Clerfayt</td>\n",
       "      <td>male</td>\n",
       "      <td>1961-12-30</td>\n",
       "      <td>59.0</td>\n",
       "      <td>2001-01-01</td>\n",
       "      <td>19</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q203312</td>\n",
       "      <td>Uccle</td>\n",
       "      <td>4.373611</td>\n",
       "      <td>50.867500</td>\n",
       "      <td>4.333889</td>\n",
       "      <td>50.803611</td>\n",
       "      <td>7638.345265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12996</td>\n",
       "      <td>Ostend</td>\n",
       "      <td>70600.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q946183</td>\n",
       "      <td>Johan Vande Lanotte</td>\n",
       "      <td>male</td>\n",
       "      <td>1955-07-06</td>\n",
       "      <td>65.0</td>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>5</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q499588</td>\n",
       "      <td>Poperinge</td>\n",
       "      <td>2.933333</td>\n",
       "      <td>51.233333</td>\n",
       "      <td>2.725600</td>\n",
       "      <td>50.854700</td>\n",
       "      <td>44570.786700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q668861</td>\n",
       "      <td>Le Rœulx</td>\n",
       "      <td>8617.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q2112675</td>\n",
       "      <td>Benoît Friart</td>\n",
       "      <td>male</td>\n",
       "      <td>1951-06-03</td>\n",
       "      <td>69.0</td>\n",
       "      <td>2006-01-01</td>\n",
       "      <td>14</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q2238127</td>\n",
       "      <td>Haine-Saint-Paul</td>\n",
       "      <td>4.100000</td>\n",
       "      <td>50.500000</td>\n",
       "      <td>4.188309</td>\n",
       "      <td>50.454942</td>\n",
       "      <td>8025.941672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q134121</td>\n",
       "      <td>Namur</td>\n",
       "      <td>110939.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q3302670</td>\n",
       "      <td>Maxime Prévot</td>\n",
       "      <td>male</td>\n",
       "      <td>1978-04-09</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>3</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q83407</td>\n",
       "      <td>Mons</td>\n",
       "      <td>4.866667</td>\n",
       "      <td>50.466667</td>\n",
       "      <td>3.951958</td>\n",
       "      <td>50.454957</td>\n",
       "      <td>64964.404059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>118241.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q240</td>\n",
       "      <td>Brussels-Capital Region</td>\n",
       "      <td>1175173.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1284089</td>\n",
       "      <td>Rudi Vervoort</td>\n",
       "      <td>male</td>\n",
       "      <td>1958-11-20</td>\n",
       "      <td>62.0</td>\n",
       "      <td>2013-05-07</td>\n",
       "      <td>7</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q272272</td>\n",
       "      <td>Sint-Agatha-Berchem</td>\n",
       "      <td>4.350000</td>\n",
       "      <td>50.850000</td>\n",
       "      <td>4.294722</td>\n",
       "      <td>50.865000</td>\n",
       "      <td>4234.864606</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   country                                    city                cityLabel  \\\n",
       "0  Belgium  http://www.wikidata.org/entity/Q118958                   Leuven   \n",
       "1  Belgium   http://www.wikidata.org/entity/Q12886               Anderlecht   \n",
       "2  Belgium   http://www.wikidata.org/entity/Q12460                     Lier   \n",
       "3  Belgium    http://www.wikidata.org/entity/Q1296                    Ghent   \n",
       "4  Belgium   http://www.wikidata.org/entity/Q12887               Schaerbeek   \n",
       "5  Belgium   http://www.wikidata.org/entity/Q12996                   Ostend   \n",
       "6  Belgium  http://www.wikidata.org/entity/Q668861                 Le Rœulx   \n",
       "7  Belgium  http://www.wikidata.org/entity/Q134121                    Namur   \n",
       "8  Belgium   http://www.wikidata.org/entity/Q12886               Anderlecht   \n",
       "9  Belgium     http://www.wikidata.org/entity/Q240  Brussels-Capital Region   \n",
       "\n",
       "   population                                     mayor           mayorLabel  \\\n",
       "0    100291.0   http://www.wikidata.org/entity/Q2324477     Mohamed Ridouani   \n",
       "1    120887.0  http://www.wikidata.org/entity/Q98000375        Fabrice Cumps   \n",
       "2     36646.0   http://www.wikidata.org/entity/Q1973059      Frank Boogaerts   \n",
       "3    262219.0     http://www.wikidata.org/entity/Q12500       Daniël Termont   \n",
       "4    133010.0    http://www.wikidata.org/entity/Q822355     Bernard Clerfayt   \n",
       "5     70600.0    http://www.wikidata.org/entity/Q946183  Johan Vande Lanotte   \n",
       "6      8617.0   http://www.wikidata.org/entity/Q2112675        Benoît Friart   \n",
       "7    110939.0   http://www.wikidata.org/entity/Q3302670        Maxime Prévot   \n",
       "8    118241.0  http://www.wikidata.org/entity/Q98000375        Fabrice Cumps   \n",
       "9   1175173.0   http://www.wikidata.org/entity/Q1284089        Rudi Vervoort   \n",
       "\n",
       "  genderLabel      birth   age start_date duration  \\\n",
       "0        male 1979-06-24  41.0 2019-01-01        1   \n",
       "1        male        NaT   NaN 2020-01-01        0   \n",
       "2        male 1944-11-16  76.0 2013-01-01        7   \n",
       "3        male 1953-05-19  67.0 2007-01-01       13   \n",
       "4        male 1961-12-30  59.0 2001-01-01       19   \n",
       "5        male 1955-07-06  65.0 2015-01-01        5   \n",
       "6        male 1951-06-03  69.0 2006-01-01       14   \n",
       "7        male 1978-04-09  42.0 2017-01-01        3   \n",
       "8        male        NaT   NaN 2020-01-01        0   \n",
       "9        male 1958-11-20  62.0 2013-05-07        7   \n",
       "\n",
       "                        birth_country birth_countryLabel  \\\n",
       "0  http://www.wikidata.org/entity/Q31            Belgium   \n",
       "1                                None               None   \n",
       "2  http://www.wikidata.org/entity/Q31            Belgium   \n",
       "3  http://www.wikidata.org/entity/Q31            Belgium   \n",
       "4  http://www.wikidata.org/entity/Q31            Belgium   \n",
       "5  http://www.wikidata.org/entity/Q31            Belgium   \n",
       "6  http://www.wikidata.org/entity/Q31            Belgium   \n",
       "7  http://www.wikidata.org/entity/Q31            Belgium   \n",
       "8                                None               None   \n",
       "9  http://www.wikidata.org/entity/Q31            Belgium   \n",
       "\n",
       "                                birth_city      birth_cityLabel  city_lon  \\\n",
       "0   http://www.wikidata.org/entity/Q118958               Leuven  4.704444   \n",
       "1                                     None                 None  4.329722   \n",
       "2    http://www.wikidata.org/entity/Q12460                 Lier  4.569722   \n",
       "3     http://www.wikidata.org/entity/Q1296                Ghent  3.725278   \n",
       "4   http://www.wikidata.org/entity/Q203312                Uccle  4.373611   \n",
       "5   http://www.wikidata.org/entity/Q499588            Poperinge  2.933333   \n",
       "6  http://www.wikidata.org/entity/Q2238127     Haine-Saint-Paul  4.100000   \n",
       "7    http://www.wikidata.org/entity/Q83407                 Mons  4.866667   \n",
       "8                                     None                 None  4.329722   \n",
       "9   http://www.wikidata.org/entity/Q272272  Sint-Agatha-Berchem  4.350000   \n",
       "\n",
       "    city_lat  birth_city_lon  birth_city_lat      distance  \n",
       "0  50.877500        4.704444       50.877500      0.000000  \n",
       "1  50.839167             NaN             NaN           NaN  \n",
       "2  51.131111        4.569722       51.131111      0.000000  \n",
       "3  51.053611        3.725278       51.053611      0.000000  \n",
       "4  50.867500        4.333889       50.803611   7638.345265  \n",
       "5  51.233333        2.725600       50.854700  44570.786700  \n",
       "6  50.500000        4.188309       50.454942   8025.941672  \n",
       "7  50.466667        3.951958       50.454957  64964.404059  \n",
       "8  50.839167             NaN             NaN           NaN  \n",
       "9  50.850000        4.294722       50.865000   4234.864606  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It appears that [Munich](https://www.wikidata.org/wiki/Q1726) has three mayors currently running, which is after double checking indeed the case. Take note that Wikidata is continuously updated and information can be incomplete for certain items.\n",
    "\n",
    "# All Mayors in Europe\n",
    "\n",
    "After collecting the data we can now explore it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>city</th>\n",
       "      <th>cityLabel</th>\n",
       "      <th>population</th>\n",
       "      <th>mayor</th>\n",
       "      <th>mayorLabel</th>\n",
       "      <th>genderLabel</th>\n",
       "      <th>birth</th>\n",
       "      <th>age</th>\n",
       "      <th>start_date</th>\n",
       "      <th>duration</th>\n",
       "      <th>birth_country</th>\n",
       "      <th>birth_countryLabel</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_cityLabel</th>\n",
       "      <th>city_lon</th>\n",
       "      <th>city_lat</th>\n",
       "      <th>birth_city_lon</th>\n",
       "      <th>birth_city_lat</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q118958</td>\n",
       "      <td>Leuven</td>\n",
       "      <td>100291.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q2324477</td>\n",
       "      <td>Mohamed Ridouani</td>\n",
       "      <td>male</td>\n",
       "      <td>1979-06-24</td>\n",
       "      <td>41.0</td>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q118958</td>\n",
       "      <td>Leuven</td>\n",
       "      <td>4.704444</td>\n",
       "      <td>50.877500</td>\n",
       "      <td>4.704444</td>\n",
       "      <td>50.877500</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12886</td>\n",
       "      <td>Anderlecht</td>\n",
       "      <td>120887.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q98000375</td>\n",
       "      <td>Fabrice Cumps</td>\n",
       "      <td>male</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.329722</td>\n",
       "      <td>50.839167</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12460</td>\n",
       "      <td>Lier</td>\n",
       "      <td>36646.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1973059</td>\n",
       "      <td>Frank Boogaerts</td>\n",
       "      <td>male</td>\n",
       "      <td>1944-11-16</td>\n",
       "      <td>76.0</td>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>7</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12460</td>\n",
       "      <td>Lier</td>\n",
       "      <td>4.569722</td>\n",
       "      <td>51.131111</td>\n",
       "      <td>4.569722</td>\n",
       "      <td>51.131111</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1296</td>\n",
       "      <td>Ghent</td>\n",
       "      <td>262219.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12500</td>\n",
       "      <td>Daniël Termont</td>\n",
       "      <td>male</td>\n",
       "      <td>1953-05-19</td>\n",
       "      <td>67.0</td>\n",
       "      <td>2007-01-01</td>\n",
       "      <td>13</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1296</td>\n",
       "      <td>Ghent</td>\n",
       "      <td>3.725278</td>\n",
       "      <td>51.053611</td>\n",
       "      <td>3.725278</td>\n",
       "      <td>51.053611</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q12887</td>\n",
       "      <td>Schaerbeek</td>\n",
       "      <td>133010.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q822355</td>\n",
       "      <td>Bernard Clerfayt</td>\n",
       "      <td>male</td>\n",
       "      <td>1961-12-30</td>\n",
       "      <td>59.0</td>\n",
       "      <td>2001-01-01</td>\n",
       "      <td>19</td>\n",
       "      <td>http://www.wikidata.org/entity/Q31</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>http://www.wikidata.org/entity/Q203312</td>\n",
       "      <td>Uccle</td>\n",
       "      <td>4.373611</td>\n",
       "      <td>50.867500</td>\n",
       "      <td>4.333889</td>\n",
       "      <td>50.803611</td>\n",
       "      <td>7638.345265</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   country                                    city   cityLabel  population  \\\n",
       "0  Belgium  http://www.wikidata.org/entity/Q118958      Leuven    100291.0   \n",
       "1  Belgium   http://www.wikidata.org/entity/Q12886  Anderlecht    120887.0   \n",
       "2  Belgium   http://www.wikidata.org/entity/Q12460        Lier     36646.0   \n",
       "3  Belgium    http://www.wikidata.org/entity/Q1296       Ghent    262219.0   \n",
       "4  Belgium   http://www.wikidata.org/entity/Q12887  Schaerbeek    133010.0   \n",
       "\n",
       "                                      mayor        mayorLabel genderLabel  \\\n",
       "0   http://www.wikidata.org/entity/Q2324477  Mohamed Ridouani        male   \n",
       "1  http://www.wikidata.org/entity/Q98000375     Fabrice Cumps        male   \n",
       "2   http://www.wikidata.org/entity/Q1973059   Frank Boogaerts        male   \n",
       "3     http://www.wikidata.org/entity/Q12500    Daniël Termont        male   \n",
       "4    http://www.wikidata.org/entity/Q822355  Bernard Clerfayt        male   \n",
       "\n",
       "        birth   age  start_date  duration                       birth_country  \\\n",
       "0  1979-06-24  41.0  2019-01-01         1  http://www.wikidata.org/entity/Q31   \n",
       "1         NaN   NaN  2020-01-01         0                                 NaN   \n",
       "2  1944-11-16  76.0  2013-01-01         7  http://www.wikidata.org/entity/Q31   \n",
       "3  1953-05-19  67.0  2007-01-01        13  http://www.wikidata.org/entity/Q31   \n",
       "4  1961-12-30  59.0  2001-01-01        19  http://www.wikidata.org/entity/Q31   \n",
       "\n",
       "  birth_countryLabel                              birth_city birth_cityLabel  \\\n",
       "0            Belgium  http://www.wikidata.org/entity/Q118958          Leuven   \n",
       "1                NaN                                     NaN             NaN   \n",
       "2            Belgium   http://www.wikidata.org/entity/Q12460            Lier   \n",
       "3            Belgium    http://www.wikidata.org/entity/Q1296           Ghent   \n",
       "4            Belgium  http://www.wikidata.org/entity/Q203312           Uccle   \n",
       "\n",
       "   city_lon   city_lat  birth_city_lon  birth_city_lat     distance  \n",
       "0  4.704444  50.877500        4.704444       50.877500     0.000000  \n",
       "1  4.329722  50.839167             NaN             NaN          NaN  \n",
       "2  4.569722  51.131111        4.569722       51.131111     0.000000  \n",
       "3  3.725278  51.053611        3.725278       51.053611     0.000000  \n",
       "4  4.373611  50.867500        4.333889       50.803611  7638.345265  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../SampleDBs/european_mayors.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How many Mayors (with birth place) are per Country in Wikidata?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5fPr1119Vu3ZtZWVl6cEHH9TFF19c6DWtj2eSNHHiROXk5GjDhg3q0KGDli9frvPPP9/xulbHMsn2HGn48OEqV66c4uLiVKpUKUdr+fnPSS107txZUv4ETHp6ui677DJJ0tKlS1WxYkXH67v1PiuSoVSSQkJCVKlSJVWqVElhYWE6cuSIRo0apYSEBN19992O1U1JSdGTTz6ppUuXSpLKlCnjWK2CunXrptGjR6ty5cry+XxKT0/Xk08+6UrtSpUquR5IJem2226TJA0aNEjDhg0LHORuu+02DR061JUxlCtXTpdccolycnI0b948rVy5UnPmzNG1116ra6+91tHa55xzju644w7FxcVpypQp2rFjh3w+n+68805HP2S3bt2q0aNHO/b9z2Tfvn3q06ePkpKS1K5dO7Vt21aDBg1yvG5YWJhCQkKUlJSka665Rh06dNDChQsdr2v1ev1XTF588UWNGjVKlStXliT99ttvgZMLJzVp0kTff/+9Iyeof0ROTo4uuugi+Xw+RUdHq2vXrurfv79uv/12R+tWqFBB/fr10+DBgxUXF6e+ffu6dqV469at6tWrV+Drpk2b6t1333Wldk5Ozkkn6AUnvJxk9TsmSTVq1JDX61VoaKjat2+vfv366a677nK8ruVrrly5soYPH67atWtLknbv3q0PP/xQd999t0aOHOnI77z18UzKvzI+cuRI/fOf/9Rtt92mG264QS+//LLjda2OZX5W50gHDx7UwIEDHfv+p+I/J7XQsGFDSdLbb78ddP7r8Xj09NNPO17frfdZkQyl8+bN07fffqsKFSqoQ4cOuvvuuxUeHi6v16vHH3/c0VAaHh6unJycwInEvn37FB7u/D/j+eefr9GjRys5OVmSVLNmTVfqSlJcXJxGjx6tFi1aBM1IubUkJj09Pei1hoeHKz093fG6q1at0jfffKN9+/bpiiuu0Msvv6yKFSvq2LFj6tOnj6MH3J07d2rhwoVau3atLrroIvXv319xcXE6ePCgnnnmGUf/7evXr6/du3ebTET4l3eVL19eu3btUqVKlQLLxp0UERGhjz/+WIsXL9YLL7wgr9er3Nxcx+tavV6/tLS0wAmcJFWsWFGpqamO161fv75Gjhwpr9er8PBw124J8CtVqpS8Xq/OOecc/fe//1WVKlWUnZ3tWL177703KHzm5uYqJSVFy5cvd+11V6lSRR999FFghn3JkiWqUqWK43UlKSoqSvv27Qv8Gyxfvjzofeckq9+xMmXKKDc3V3Xq1NG7776rSpUquXYFy/K4snfv3kAglaRatWopOTlZ1atXd7y21fFMUmDlWpkyZXTw4EFFRUXpt99+c7yu28eygpKSkrRw4UKTc6T69etr165dio2NdazG6Vgujz927JhSUlICv0/79+935VY+t95nIT63jpKFaMaMGWrfvv0p7/dy+mT6hx9+0EcffaTdu3fr4osv1ubNm/XII48ElosUtvXr16tx48anvWfCjWB4uplGN34BJWn27Nn67rvv1KJFC0n5YfHSSy/VLbfc4mjdsWPHqn379oEZqoJ+/PFHXXTRRY7VHjRokDp06KBLL730pGXaixYt0uWXX+5Y7Y0bN2rYsGGqVKmSSpUqFQgMbiy3XLBggVq1aqVdu3Zp3Lhxys7OVteuXR29507Kn/hYsmSJ6tWrp/j4eKWmpmrDhg264oorHK1r9Xr9Jk+erH379qlNmzaS8u8RqlGjhu6//35H6/7jH/9Qv379zO4p3bZtm2rVqqUjR47oww8/VFZWljp37qz69es7VtPn8yktLU3VqlVzrMaZZGZmaubMmfrpp58kSfHx8brtttsUGRnpeO2UlBRNnDhRmzdvVvny5RUTE6PevXsrJibG8dpWv2MHDhxQxYoVlZubq88//1xZWVm6+uqrHb/FSLI9rowaNUpRUVFBx5SMjAz17t1bzz33nIYMGeJYbavjmSTNmjVL1157rX788UdNnjxZISEh6tChg+644w5H61ocy/zGjBmjDh06mJwjPfnkk9q3b59iYmJcP08ZNWqUatasqaVLlwYtj+/evbvjtdetW6cJEyaoevXqgT4BPXr0UJMmTRyt69b7rEiGUim/e2N6enrQDc5ufdgfPnxYW7dulc/n0wUXXKAKFSo4VmvGjBnq2rWreTC0tn37dm3atElS/slU3bp1Ha3n9Xo1ePBg15Y8nU169+6tbt26nRQYnG76AxsrVqwIBJWGDRuqZcuWjtccNGiQBg0a5NoSzrNF37599corr1gPw0x2drZ8Pp/j95vBTk5OjubPnx/4vL7wwgt19dVXq1SpUic1bHSCxfHsRMePH9fx48ddb1BYkhw4cOCUj7txntKvXz8NHz5c//znPzVy5Ejl5uZq0KBBeumllxyvLeW/v/bs2SNJOvfcc127p9YNRXL57n//+1/NnDlTFStWDJw0uzVDsnLlSjVu3DjQLOLIkSNauXKlYwe+rl27SrIJn59++qluvPFGvfXWW6d83o3ZR786deqoUqVKgUmI1NRURychQkNDFRISoqysLFc/WE53j5mbs4AVKlQINJVyi//q7+m62znV1e7EZZUncmpZpdXrPZVWrVq5thTfLyYmRi+88IKaNGkS9IHq9OueOnWq7rvvvtN2MnS6g2HdunW1bds2VxqgnCg5OVmfffbZSV213Zh4e//993XjjTeqfPnykvKv2s6dO9fRq0hWv2OjRo1Snz59Tnssd/IYbn1c8Xq9GjJkiAYNGqQbbrjhpOedDqSS+8czq9Vs1scyybbDdHR0tDZt2qS9e/eqffv2ysjIcG3ZsvVtN9u3bw8cx3fu3ClJjq3qcvt9ViRD6eeff65XX31VUVFRrteeOXNmUAAtX768Zs2a5VgotWxB7e/W5+/4a+WLL77QrFmzVLFiRYWGhroW0CIiItS3b18lJCQENbRyMoy7ccP676lbt65ee+01NW/e3LV7iP33RLjd3e7tt9+WJH3wwQeqXLmyLr/8cvl8Pi1ZssTR+4GsXu+JrLZ7iomJUUxMjHJzc125d9fPv+zd38nQbdu2bdMzzzyj6OholSlTxtXJptGjR+vKK69Ux44dXb9CvW7duqAGP5GRkVq7dq2jodTqd8y/hM/iWG59XLGazPWzOJ5t3LhRjRs3DnQAPpFTn5vWxzLJtsP0zJkz9fPPPwdCaW5urt544w0NHjzY8dqdOnVSZmambr/9dg0fPjywPN4Nb7zxhlJSUlSnTp2g47hTodTt91mRDKXVqlUzWxZxqtXOBWedC5vlSav/alm7du3MxiDlN7aymIRo2bKl60t/zoYlsjk5OSpVqpR++OGHoMedDKVXXnmlJLvudqtXr9aIESMCX1911VV66qmnHOtgeOWVV8rr9aps2bKuXhU9kdV2T/6fs39m240rKFL+BJvX61ViYqIee+wxV2oW5Ha3yIJCQ0Ndu1f5RF6vV8ePHw9McuXk5ATtdecEq2OKv9HO7t271bRp06DnvvzyS0d/BtbHUclmMtfP4njmDyO9evVydbLHf7Fgx44duu6664Kemzdv3inv83SCVYfplStXavjw4YErdVWqVHHtfLljx46S8peHu7EfbEHbt2/XqFGjXOvF4H+fufV+KpKhNCYmRs8//7yaNWvm6tIvKf8HNG3aNF199dWSpPnz5zt6JdHyw8UvIyNDn3zyifbs2RPUacyt+y2tJiEsw7jlshjL+5QzMjKUmJh40hJDp8dUpkwZLV68ONAgY+nSpY5v9xQaGqqlS5eahlKr7Z527dqlMWPGKDMzU1J+d9ZHH300qGunU0JDQ3XgwAHl5ua61sHczz/pdOjQIcdD2YmaN2+u+fPnq2XLlkGfm240Omrbtq3+/e9/q3379pKkhQsXOt5EzM/qmPLRRx+pVKlSaty4saT822E2bNjgysSA1WuWbCZz/ayOZ1J+87YmTZqodevWaty4sWuh4dtvvz0plH7zzTcnPeYEyw7T4eHhCgkJCfw7u7V0Vzr1Ckb/nql16tRxtHbt2rWVnp7uWvdyv02bNmnmzJlKTU1VXl5eYBVCYYfyItnoaObMmad83I0Al52drY8++kg//vijJCkhIUG33HKL4zP9KSkpmjJlirZu3aqQkBDVr19f3bp1c6XN+osvvqjWrVvrs88+U48ePfTNN9+oQoUKjm69U9D48eOVnJzs+iTE3r179f7772v37t1BJ5BuzIw9/fTTp1wW48YMpGVTrWeeeUYNGjRQXFxc0KzzJZdc4mjd/fv3a+rUqdq8ebOk/OYc9913n+PdQadOnaq8vDy1bt06KAS7tWR+ypQpSk9Pd327p2eeeUZ33HFH4IR9w4YNmj59ul588UVH6/qNGTNGe/bsUfPmzYOO3U4fU5KSkvT222/rt99+U4UKFZSamqpzzz1Xo0aNcrSulH/SfCInTipOZ926dYHVFwkJCY53i/SzOqZkZGRo2LBhuvvuu7Vu3Trt2bNHTzzxhCsTIVav2ZrV8UzKXzq9evVqLVu2TL/88ouaNWumNm3aqEGDBo7UW7JkiZYsWaLNmzcH1cjOzlZISIiee+45R+oWZNlhes6cOdq3b59++OEH3XTTTVq4cKHatm3r+P7xkvTaa69p+/btat68uaT8lVbnnXeeDhw4oEsuuUQ33nijY7VfeOEF7dixQ+eff37QscTpe4ifeOIJdevW7aRjSmGvYCySV0qtl6b8/e9/d73u66+/rquvvlpPPfWUpPwrOa+99pormzMfPnxYHTp0CCwJadiwof71r385XtevWrVqqlatmuv3n40bN05du3bVtGnTNGDAAC1cuNC1WUDJblmMv4mXlN/lbeXKla7Nyh07dsy1yY6CYmJi1K9fP9fr+psUzJgxI+hxt1YhHD16VGXKlHF1qbaU/3P2B1JJatSokSt7rflVr1490FLfzVskPvzwQ7300ksaPHiwhg8frvXr12vx4sWu1B47dqwrdU7n3HPPVWhoqBISEnTs2DEdPXrUlS68VseUChUqqF+/fho8eLDi4uJO2/jICVavWcqf/DjV63Rj8sPqeCblXzVs3bq1WrdurczMTE2dOlWDBg3Shx9+6Ei9Cy+8UJUrV9bhw4eDmkpFRETovPPOc6Tmifbt26eKFSuqXLlyrp+Xd+7cWT/88IPKli2r5ORk3X777UpISHCl9sGDBzVs2LDAhGbXrl01ZMgQvfDCC+rfv7+jodQq/5QrV+6k2xGcUCRDaUZGhj799NOTNq5140TOqoPhsWPHgvamvPzyy/XZZ585WtPPPxtTuXJlrVmzRpUrVw4su3OD1S9hTk6OLrroIvl8PkVHR6tr167q37+/Y/cZFmS5LObE2fQ2bdq4Musq5S8xXLNmTVAwdoPVcrdevXqdtNohJSXF0ZoFWS3VjomJ0axZswLHtMWLF7uyZ6Wf1TElLCxMUVFR8vl88nq9aty4sStL8v127dp10soPN5bRJiYmasGCBcrMzNQbb7yhgwcPatKkSa4cV9w+ppzY0Ts3N1cpKSlavny5K03EJLvjqCQNHTo08Ofjx4/ru+++c+18wXqLvI0bN2rZsmVat26d4uLi9OSTTzpWKzo6WtHR0a5tQ3Iq3377rd58801FRkaqQYMGio+PV4MGDVy5JUDKX3HhVhAt6NChQ0FXKcPCwnTo0CGVLl3a8e1Z3Lq380SNGjXSO++8o1atWgW99sJe1VUkQ+nrr7+u1q1ba82aNUHLSd3gdgdD/8G8SZMm+uSTT9S6dWuFhIRo2bJlrsxaSNItt9yirKws3XPPPZoyZYqysrLUrVs3V2pLdpMQpUqVktfr1TnnnKP//ve/qlKlimv3LTz66KPyer26//779fnnnystLU19+/Z1pfaJ9u3b51q783nz5unjjz9WeHi4wsPDXesGO3z4cDVo0EAXXXSRq80qRo0apWHDhv3uY07JycnR119/fdLvltMndw8//LBmzJgR2LOzQYMGevjhhx2tWZDVMaV8+fLKzs5WfHy8Xn/9dVWsWNHxe5f9Zs6cqY0bNwYa8Kxdu1YNGjRwJZTOnz9fQ4YM0YABAyRJ55xzTrE9pvg7eluyOo5KJy/n+9vf/ubaZK7V8UzKv0Jcp04dXXrppbr77rtda95m2X/i0UcflZR/5XD58uWaPHmyfvvtN33wwQeO1bTaxq2gtm3bauDAgYFmoKtXr1bbtm2VnZ3t+D3NVj/vbdu2ScpvtFRQYX9mFslQarmc1O0Ohv3791dISEjgKtlXX30VeC4kJMSV5Zz+dfOxsbGuLSssyGoS4r777lNOTo66d++uDz/8UOvXrz/lfVlOWLVqla677jqVLl06cFVn3rx5rjQv8B/0/ScylSpVcm3JutUJndvL3fbs2aNff/1VWVlZQfvbHT161NUGOGPGjFHNmjX1/fff69Zbb9WSJUsCW0E5KTIy0tV9jk9kdUx56qmnVLp0aXXr1k2LFy9WVlaWunTp4nhdSVq+fLlGjBih/v3765FHHlF6erreeOMNV2qXKlUqaHY9Ly/PtaWsliExMzNT+/btCwpIblzpsHzNBU9afT6ffv7558D+4k6zOp5J+aH0xJ/tpk2bHLun1M9yW5ZFixZp06ZN2rVrl6KionTNNdcoPj7e0ZpW27gV1KVLFzVt2jTQg6JHjx6qV6+eJDne1d3q5+3WuX+RDKWWy0nd7mBofR+QZNtkSbKbhPBvcB8REeH6siDLjnrWM/0WJ3JuL3dLTk7WmjVrdOTIkaD97SIiItSzZ09XxiDlXwXv06ePkpKS1K5dO7Vt29bRD5/TbcDt58aG75LdMcV/9SQrKyswy+6W0qVLKzQ0VKGhocrKylLFihWVlpbmSu2GDRtq9uzZysnJ0Q8//KD58+cHJjvdYHFMWbBggebNm6eDBw+qTp062rJli+rXr+/KyZ3P59PixYu1f/9+denSRampqUpPTw98pjnpnXfeCfw5NDRU0dHRji5jLcjt41lB06ZNO2mFy5QpU1xZ9WLVf2LatGmqXr26rrzySjVq1MjVWzDc3satoNTUVFWsWDGoy3RqaqqqVavmeG3J5uedlZWlmTNn6qeffpKUf/zs0qVLoe+MUSRDqeVy0m+//VZSfucvPzc6GPrrnsiNpVeWTZYku0mIU51AlytXTvXq1VOnTp1UunTpQq/p76i3f//+oA+z7Oxsx+/T2LNnj84999yTlmf4udER1upEzu3lbi1atFCLFi0Cr89KWFiYpPxlpbt27VKlSpUcXVbp34B7xYoVSk9P12WXXSYp/5hSsWJFx+qeyOqY8tVXX2nGjBkqXbp00GoEN5rA1KtXT0eOHFHHjh319NNPKyIiwrX33l133aWvv/5asbGx+uqrr9S0adPAXn9OszymDBkyRAMHDtSgQYO0Z88eTZ8+3dGafm+++aZCQkK0YcMGdenSRREREZo8ebKGDBnieG2L1VR+bh/PpPzllJs3b1ZGRkbQViFZWVmuXCG27D8xefJk/frrr/rpp5/0wQcfaO/evapZs6Z69+7teG2Lbdz8hgwZEjg3zMnJ0f79+1WzZk1Xuqhb/bzHjRun2NjYwATTokWLNG7cOP3zn/8s1DpFMpRaLie1unL5888/B/6ck5Oj9evXq27duq6EUssmS5LdJET16tWVkZEROOgtW7Ys0OltwoQJjhx4LTvqzZ07Vz179gya6S7Ijd81qxM5q6vDK1euVK1atVS6dGm9/PLL2rlzp7p16xb0++akTp06KTMzU7fffruGDx+u7OzswGbwTvBfnXr77beDGqJ4PB49/fTTjtU9kdUx5bPPPtMrr7ziWg+Egh588EFJ+VcUmjRpoqNHj7rWpTM0NFSXX365GjZsqJo1a7pS08/qmFK6dOnAxOXx48d17rnnKjk52fG6Uv79X8OGDQt0FI+MjHStc71bV1ROxe3jmZTfyCo7O1t5eXlBnbzLlSunPn36OFpbsu0/kZWVpdTUVB04cEAHDhxQVlaWa8vyH3vsMU2dOlVTp06VlH/u5PTSWT9/LwS/7du368svv3SlttXPOyUlJSiA3nbbbYELVYWpSIbS/fv364svvjipU6ZbS78sOhieeP/VkSNH9Oqrrzpa0+90TZb8VxacvoJnNQmxZcuWoJllj8ejf/3rXxoyZIhjHzaWHfX8y0YtZ7otT+Qslvh9//33uvvuu7Vy5UpFR0frn//8pwYNGuRaKPVfrWrYsKFr+1VK+RNdKSkpgVsA9u/f7+qWMFbHlOrVq7s2m+93upUP/ufcWAGRlJSkd955R7m5uRo7dqx27NihDz/80JXPbKtjSpUqVXTkyBG1aNFCL774osqXL6/o6GjH60r5Vwy9Xm8gIGRkZLgWFty6onIqFscz//L/du3aufbzLSg6Olq5ublKTU1Vq1atVLNmTVf2wpWk5557Tg0aNFCDBg10zTXXqGrVqq7Uley2cTuVuLg4bd261ZVa/vdYwX4jbihdunTQPdKbNm1yZLVgkQylI0aMUPv27dW8eXNXO2VKth0MCypTpoz279/vSq3vvvtOUn5bf0mBpQJLly51dOnZW2+9dcbnnW6Ukp2dHXSfQGpqaqD7rlMH/dN1lnOze2LBxjt+5cqVU2xsrONLLK1O5KyW+Pkn1dasWaNLL73UlasJkoKWmZ3K9ddf72j9bt266fnnnw/sFZqamqoePXo4WrOgUx1b/EvzW7Ro4Vjdu+66S88884wuuOCCoGOIk8ey06188HMjlM+cOVNDhgzR888/L0mqU6eOa59fVscU/1WErl27auPGjcrKylKTJk0crytJ1157rUaMGKFDhw5p+vTpWr58ue644w5Xart1RaUg6+OZlH9O9s4777je0XvDhg0aO3Zs4D2dmpp6yqZLhc3r9SohIUH33nuvo3VOJzk5WW+++aYOHTqkV155RTt37lRSUpJuvfVWx2sXfL95vV798ssvqlKliqM1f2+f45EjRzpav0ePHho7dqyysrIk5S+Rd6LxZ5EMpaVKlXKl4cupWHUwLHh/o9fr1Z49e3TppZc6WnPbtm2qVq1aYMnyN998oxUrVgT27HT6CqkbM/hncs899+jZZ59VjRo15PP5tH//fj344IPKzs52bBLCusmQJH399dfasmWLGjVqJCl/77W4uLhA0wwnr+JZnchZLfFr3ry5nnjiCZUuXVoPPvigMjIyHN/nTFLQMjMLTZo00euvv649e/ZIks4991xXXrff8ePHlZycHNiTd8WKFYqJidHOnTu1YcMG3XfffY7UnThxoho3bqzY2FjXrlxZrnzwCw8PP2nCxa3Xb3VMeeutt9SmTRtdeOGFru8teNlllykuLk4//vijpPx/A6e3qvBz64pKQdbHM8muo/fbb7+tZ555JrAsPjk5Wa+99prjDZZCQ0MD3WctTJgwQffcc48mTpwoSTrvvPP0+uuvuxJKC77fwsLC1KxZM7Vq1crRmm7e3nIq5cqV04gRIwKhtFy5co5MLBbJUHrddddp5syZuvjiix3dxPVUrDoY+huESP/raOf0UolJkybp2WeflZQfTKZPn67u3btrx44dmjBhguPr2Nu1axf0tf8qpVv7fzVr1izoxLlmzZqBD9e//e1vrozBgtfr1ejRo1WpUiVJUnp6usaOHauXX37ZlaWlmZmZSktLU0REhCIiIrRr1y7Hf7etlvj9/e9/14033qhy5copNDRUZcqUcWVJ0m233Sav16t58+a5chXhRCdejU9JSXHtaryUfwvG4MGDAyttrrrqKj333HMaPHiwo8e1vLw8V/d4PtHmzZtPuu3FjVU+tWrV0pIlS+T1erV371598cUXrjVZSk1NDfzZ3x00PT3d8U6ZcXFxmj17tpKTk9WiRQu1adMmsG2E0/yB+JprrnGlXkEFr6j4fD5FRkY6vpWam8sYT8eqo3deXl7Qfdo1a9YM+v12Up06dTRs2DBdeumlQbclOB3QpPzeKid2k3Zr5WStWrVOuij03XffOXqhqODqjgMHDmjv3r1KSEhQTk6OKz/vV155RcOGDQuaXPQ/VpiKZCjdtWuXFi1apPXr1we9Cd2YEbbqYNiwYUOlp6cHNrCtUaOG4zW9Xm/gauiyZcvUsWNHXXLJJbrkkkscX45T0K5duzRmzBhlZmbK5/OpQoUKevTRR1W7dm3Ha2/fvj1wErdz505J7pzEWUpNTQ0EUkmqWLGiUlNTFRkZGehu6JQPPvhA3377rWJiYlz93bZa4mfZVTs0NFRLly41CaX+q/GNGzeWz+dz9Wq8lD/xkZ2dHfiAPXbsmDIzMxUaGuroFdsmTZooMTFRzZs3d2VLsYLeeOMNpaSkqE6dOkG/W2681+6//37Nnj1bpUqV0uuvv66LL75Yt9xyi+N1pf91yvT5fDp+/LhrnTLbtWundu3aKTMzU8uXL9d7772n1NRUvf76647WlWwDcZ06dU66ouIWyyWdVh294+Li9J///CfQyXzx4sWurTI7fvy4oqKitH79+qDH3QilUVFR2rdvX2DFxfLly1W5cmXH60rSJ598clIAPdVjTkhMTNSCBQuUmZmpN954Q2lpaZo0aZKee+45R+q5vad6kQyl3333ncaMGePazdx+Pp9PN910k8qXL+96B8MFCxZo1qxZgZO4KVOm6NZbb1WHDh0cq+n1epWXl6ewsDCtX79eDz30UNBzbpk4caLuvfdeNW7cWFL+PRQTJkzQiy++6Ghdy5M4S40aNdLQoUODljY2atRI2dnZKl++vKO1v/vuO73xxhuu/25bLfGz7Kot5XcsnDx5slq3bh000+30SY311fgbb7xRTz31lBo1aiSfz6effvpJN998s7Kzs3XRRRc5Vnfp0qWSpI8//jjwmFtbwmzfvl2jRo1ybdmsn9fr1dChQzVo0CDdeeedrtaWbDtlSvl7ZyYnJ+vAgQM699xzXalpGYgPHz6smTNnBpZ2NmjQQF26dFFUVJTjtS2XdFp19O7Ro4fmz5+vL774QlL+v/fVV1/teF1Jru/fXtADDzygiRMnas+ePerZs6diYmIc7767du1arV27VgcPHgzqS3D06FHXrtLOnz9fQ4YM0YABAyRJ55xzjqPbHrm9p3qRDKW1a9fWkSNHXN3XTso/eRgyZEjgQ87NjYLnzJmj4cOHBw7shw8f1jPPPONoKG3Tpo2ef/55RUVFqXTp0oqPj5eU/yHr5uznsWPHAoFUyg9NbnTqtDqJs/bAAw9oxYoV2rRpk6T8EN6qVSuFhIQ4fsXS7d/tU81kx8bGSnJnb1jLrtqSAlf/Z8yYEfS40z9ny6vxktShQwc1bdo0sPLkzjvvDDSquOeeexyra7WlmJT/u5Wenu7a1QS/0NBQhYSEKCsry9XPjdNxq1Pmu+++q5UrV6p69epq3bq1br31Vscn9U5kEYhfffVVxcfHB5bBL168WK+++mrgViAnWS7pPFVH788//9zRml6vV0899ZReffVVkxUvaWlpeuutt4ImILp37+5KF97q1avr2WefVXZ2tnw+n8qWLet4zcqVKysuLk5JSUlBE7dly5Z17baMUqVKBU3a5+XlOXqO6vae6kUylGZlZemJJ57Q+eefH/TDcaO9fN26dbVt27aTDnxOi4qKCvqlK1u2rOMzj7fccosaN26s9PR0JSQkBDVa6t69u6O1C4qJidGsWbMCV08WL17syoSA1UmctZCQkMAybbfdfPPN6tevn2JjY1353e7fv39gaZ+f/2u3rmAV5GZXbcmuCY7V1fgTt0fxnzylp6crPT3dlWVvVvd1Hj58WH369DH53IyIiFDfvn2VkJAQdEXe6Q7qkk2nTCn/pPnFF1802ZPWMhCnp6erS5cuga9vvfVWLVu2zJXalks6T2Xu3LmO9p8IDQ1VzZo1g3YJcNO4cePUtm3bwBZ5ixcv1rhx41yZgOjdu7cuuOACNWjQQPHx8a7czlWnTh3Fxsbq+++/P6nniVsaNmyo2bNnKycnRz/88IPmz58fmBBxklt7qhfJUOr0Zshnsm3bNg0cOFAxMTEqU6ZM4OTV6XbMNWrU0IABA+TxeBQSEqKkpCTFxsYGPnCdmiU71cyI25ufP/zww5oxY0bgCnV8fLwefvhhx+tansRZOBu2oxk7dqxuvPFGxcbGujLDPXbsWPl8PqWlpZl8qFt01S4oPT1d06dP12+//aYBAwZo9+7d2rJli6MrMCS7q/HW26NY3hJg2QymZcuWatmypaT/dd0tOBHkJItOmZJ05ZVXKikpSRs3bpSUfzLp8XgcryvZBuKEhAQtXbo0cBxbvny5Lr74Yldqn2pJZ+/evV2pbeXIkSOB85SCEz5unKdkZGSoffv2ga/btWvn+NVhv1GjRmnr1q3atGmT3n33XSUnJys2NtbxfiehoaFKS0tTbm6u67cZSfnNERcsWKDY2Fh99dVXatq0aWB/Xie5tad6kQulXq9XEydOdHWJm6TATNTAgQNdretXvXr1wEbzkgIfbmdDK3Sn5OTk6KuvvtK+ffsUGxure++919WDwNnQ0c9NZ8N2NGXKlHF9u6cTl+W76cSu2l6v17WrClL+THe7du0C9ziec845Gj16tOOh1OpqvPX2KJa3BLi9LYkkrVq1SmlpaYEusP/617+UkZGhkJAQ/f3vf3dlDFbH8ffff1/btm1T27ZtJUlffPGFtmzZorvuusvx2haB2D+p6fP5NG/evMBWeT6fTxEREa7sZ2mxpNPKvn37lJ6erttvvz3o8Z9++sm1q8NRUVFatGhR4D2+ZMkSV+4dlvI/L8PDwwO3B1SoUMG1235iYmL07LPPqnnz5kG7QTi9hNrr9apPnz569dVX1alTJ0drncitPdWLXCi1Wq4wYsQIDRs2TNHR0Ro5cmTQ5tBu8H+wHjt2LGg2rDgbO3aswsLCFB8fr7Vr12rPnj2O7R94KhYncWeLTZs2ae/evWrfvr0yMjKUnZ3typLpBg0a6P3335fH43F1uyerZfkNGzbUL7/8oiVLlmj58uWKiYlx5SqO3+HDh9W6dWt98sknkvKvJLlxhXrFihV67733Ag0a3LwaL9l1Pba4JeDZZ5/V4MGDT1oJ4ca/+Zw5c/T4448Hvs7NzdWwYcOUnZ2tcePGubIqIDk5WZ999tlJS6adnqBYs2aNhg8fHvh9ateunfr16+dKKLUIxGfDpOb777+vG2+8MbBUOTMzU3PnztUdd9zhWM0zrTDKyclxrO7UqVN11113BXog+EVGRur99993fGJRyl/F9tZbb2natGkKCQlR/fr1XWt+1K1bN8XGxur6669Xx44dXQvD0v8uEvl8PlcvDFku13ZrT/UiF0olm+UKBZcauXnPl9+WLVs0fvx4ZWdna/z48dqxY4cSExP14IMPuj4Wt+zevTtw9apDhw6BbmNuKfhhk5ubq9zcXEVERLh24mxl5syZ+vnnnwOhNDc3V2+88YYGDx7seO0dO3ZI0kmNSJw+gdy2bZueeeYZRUdHu7IsPzk5WUuXLtXSpUsVFRWl1q1by+fzuX4lr0yZMjp8+HDgfb5lyxZXmtG8++676t+/v2rVquV4rVOx6npscUuAvyOlRWjIzc0NOnlq0KCBIiMjFRkZ6UqzOkkaPXq0rrzySnXs2NG1pjd+WVlZgWZp/i1S3GAZiKX8BmonTgK4Mdm2bt26oNcYGRmptWvXOhpKrcL4oUOHTgqkUn6jpQMHDrgyhujoaLPbmR5//HFt2rRJ8+fP14IFC3ThhRcqPj7e0e7pfv6LRNnZ2ZIUdLXUaVbLtU/cU7106dKO7KleJEPpicsV3FBwJsxi6dXUqVM1cOBADR8+XFL+Ddc//fST6+NwU8GTNjc6cp6o4IeNz+fTqlWrXOnaaG3lypUaPnx44CBXpUoV12YDrZZXur0s/8knn1SDBg309NNPB/YcdutenILuvfdeDR8+XPv27dOzzz6rjIwMPfnkk47XrVSpklkgley6HlssJR05cmRgg3O3V/mc2N36gQceCPw5IyPDlTGEhobqqquucqVWQTfddJP69esXtO2QW0uWJbtAPG7cOO3atUu1atUKmgRwI5R6vV4dP348cAUnJyfHkb0UzwZHjhw57XNOXqGVpFmzZp3x+YKNrpzi7wq7Z88erV27VvPmzdOnn36q9957z/Hau3bt0pgxYwLHt6ioKD366KOuNFtyO/98+umnuvHGGyVJP/74Y2B1S0REhGbPnl3oE11FMpQ2bNhQBw4c0N69e5WQkKBjx445vm/mjh071K1bt8CSDH/7ZzeXnZ14ud7tWV+3+f/NJQX9u7u91E/Kn4ho2bKlZs2a5eqJhYXw8HCFhIQEJl/8s4FuyMrK0syZMwMTLg0bNlSXLl0cv3oXHR19yiXLTunbt6+WLVumF154QRdffLHatGnjWuOXguLi4vT8888rOTlZPp9PNWvWdOW+7bi4OI0ePVotWrQIWgLk5tLlgtzqemzx2WW5yueCCy5QYmLiSfc/ffXVV6pXr56jtf0njM2bN9f8+fPVsmXLoPea09s9tW3bVo0aNQpclb/77ruDtkFykmUg3rp1q0aPHu1KrRO1bdtW//73vwPNdxYuXFhs9xWPi4s75e/WggULHL/d5VS3kB07dkxff/21Dh8+7EooHTlypHbu3KkaNWooPj5ejz76qGu330ycOFH33ntvYKvCDRs2aMKECXrxxRcdr+32bWXLli0LhNJPPvkk6JaL77//nlAqSYmJiVqwYIEyMzP1xhtv6ODBg5o0aZKee+45x2p++OGHjn3vP6Jq1aravHmzQkJClJubq3nz5rm275gV63/zFStWBP7s8/n0888/O7KG/mxz6aWXauLEiTpy5IgSExO1cOFCV7q7Sfmz7LGxsYGrdYsWLdK4ceMcv7rj9pJlfzfS7OxsJSUl6fPPP1dGRoYmTZqkli1butatsnfv3rrhhhuCriQNHTpUTz/9tKN1jx49qjJlyuiHH34IetytUFqw67HP59Pu3btdub/R4rPLcpVPt27dNGLECC1dulR169aVlN/s6fjx4453yTxxu6c5c+YEnnNyu6cTtx3ybz9z8OBBHTx40JVthywDcf369bV7926TlRA33XSTzjvvPP3444+S8rejadKkievjcMN9992nkSNHasmSJYH31M8//6zc3FzHf7duuOGGwJ+PHj2qefPmaeHChWrdunXQc07Ytm2bqlWrpptvvll169bVokWLtGLFCqWnpys2NlalS5d2tL6UH8D9gVTK3+LM6dsRrHZHKDipeeLEuRMT6UUylM6fP19DhgwJ3GN4zjnnBBpmFFc9evTQ1KlTdfDgQfXq1UsJCQnF+n7Ss8Hq1asDfw4NDVVMTIwja+jPNp07d9YPP/ygsmXLKjk5WbfffrsSEhJcqZ2SkhIUQG+77TbHP2AluyXLERERatu2rdq2bavMzEwtX75cn376qWuhNCwsTBs2bNC2bdv00EMPKTw8XAcPHnS8rlvNME7nxK7H0dHRrmz4bvHZZbnKp2LFinrxxRe1fv16/frrr5KkZs2aBZ3QOWXs2LGS8pcynnii6uTyRstth86GQHzFFVdo4MCBqlSpkkqVKuXatnl+TZs2VdOmTV2pZalSpUpmv1vS/5pILV68WFdccYWGDRvm+OoDSZo0aZKeffZZ1atXTxs3btT06dPVvXt37dixQxMmTFDfvn0dH0NMTIxmzZoV2A5l8eLFjjeCtLp3+UyTmk5MchbJUFqqVKmgJWZ5eXkm93m6qUKFCoGGFVL+AeHLL7/ULbfcYjiq4s36xNlSQkKCEhISlJGR4WpXu9KlS2vTpk1q0KCBpPwuwG7MfFouWfaLjIxUp06dXG31XqZMGT355JP69NNP9dxzz6lPnz6OHkv996e89dZbp3z+xHs9nVJwCZSb73GLzy7rFSeS1LhxY9dOlk/07LPPBu6pPdNjheXvf/+7qlatGuiw/M0332jFihWKjo52fI916314JWn8+PHq3bu3YmNjXTsvOxv22LZi8bv1zjvvaOXKlerYsaNeeeUVVxv9eL3eQPhdtmyZOnbsGNhezI0JbCm/6/CMGTMCjTjj4+P18MMPu1LbbWea1HTifu0iGUobNmyo2bNnKycnRz/88IPmz5+v5s2bWw/LEampqfroo4/022+/qWXLlmrdurVmzJihRYsWqU2bNtbDK5ZOd8Ls59aJs9u2bNmi999/X5GRkbr11ls1ZswYZWRkyOfz6dFHH3VlGVSPHj00duxYZWVlyefzKTIyUv/4xz8cr2u5ZNmSf/nNjTfeqLp16+rFF188qTlNYfLfcuDGFZtTsX6Pl6TPLmvp6ek6ePCgcnJy9MsvvwTe60ePHnV0qZ3/So4k16/kWAZivwoVKji+J+qJzobtaEqSuXPnKjw8XLNnzw7scS25Mwng9XqVl5ensLAwrV+/Xg899FDQc07KycnRV199pX379ik2Nlb33nuvKz0YLLk9qVkk/zXvuusuff3114qNjVViYqKaNWtWbE8gx44dq/j4eLVq1Urr1q3TZ599pvPOO08jR4507R6RkqbgCfPMmTPNNl9321tvvaU777xTWVlZ+ve//61//etfql+/vvbs2aPXXnvNlVBap04djRgxItAtMiIiQkuXLtV5553naF3LJcuWCp6oJiQkaODAgafdw7Mw+Ju1tWvX7qTnvvzyS8fq+lm/xwt+dn311Vdq2rRpsf3ssrZu3Tp9++23SktLCwotERERuvPOOx2ra3klxzIQ+9WtW1evvfaamjdvflY0MUPhs1x90aZNGz3//POKiopS6dKlFR8fL0nat2+f4w0Rx44dq7CwMMXHx2vt2rXas2eP7rvvPkdrljRFKpSuWrVKaWlpuuaaa9SpUyctWLBAGRkZ2r59u8qXL69LLrnEeoiFLjMzM3Di2KRJE/Xq1UuPPfZYse+8a6ngCfO8efNOeQJdHOXl5QXuZZwxY4bq168vSa401MrKytL8+fN18OBBtWjRQhdddJHmz58fmIS57LLLHB+Df8lySTJv3rygqxrR0dHauHGjY/VGjhypPn36nHSldMaMGVq9erXjW3dYvsel/PtX/U2uKlSo4ErNkqpdu3Zq166dli9f7uq5geWVnLNhaWNOTo5KlSpl1sQMxdstt9yixo0bKz09XQkJCYFl216vV927d3e09u7duwNLdjt06BDoDYDCU6RC6Zw5c/T4448Hvs7NzdWwYcOUnZ2tcePGFctQKgXv9RYVFRW055gbN5aXZMX9XuWCCk50nHgfp9P/DmPGjFH58uVVv359JSYmavbs2fL5fHrqqadUp04dR2tL+Z2W33vvvUDTmeJ+L1JOTo5ycnJ0+PDhoONLVlaWo42O+vTpo1GjRumxxx5T/fr15fP5NGnSJO3du9eV+92s3uM+n08zZ87U/PnzA8EkNDRU1157rSvbJ5REixYt0uWXX64DBw5o7ty5Jz1//fXXO1LX8kqOZSD2K8m9GOAO/2RiQTVr1nS8bsGlumFhYY7XK4mKVCjNzc0N2quzQYMGioyMVGRkpOPtmK1kZWXp6aefDmq97O8Q6mRbe5Q8bt/QXlBKSkpgBrJjx4566KGHNG7cOFeaHEnSu+++q/79+5tsY2AhMTFRn3/+uX777bfA8USSypUrp2uuucaxunFxcXrqqac0cuRIPfDAA0pMTJQkDRgwwJXtlqze459//rk2b96sIUOGBLo0pqSk6M0339TcuXMdC0glmf+c4FRNy5ycgLC8kmMZiP2Sk5P15ptv6tChQ3rllVe0c+dOJSUl6dZbb3WlPuAU/+eHpKDPkOI+ie2mIhVKT2zA8cADDwT+nJGR4fZwXOFvaw/3FOzkd+zYMVe3ULBkeZ9IwRnI0NBQVa1a1bVAKuW31y8pgVSSrrvuOl133XX64osvdO2117pWNzMzU1WrVtU//vEPjRgxQhdddJHuv/9+HTt2TMeOHXN85YfVe3zRokV65plngpbsVq9eXb1799aLL75IKHXAlVdeKUmn7Anw+eefO1rb6kqOZSD2mzBhgu655x5NnDhRknTeeefp9ddfJ5SiyDsbOpkXd0UqlF5wwQVKTEw8acuEr776SvXq1TMaFYobOvm5z2oGcsWKFZLyr+CNHj1aLVq0KBHNOdavX6/GjRurSpUqgX+Dgpx63f379w+cKEdERGjr1q0aMGBA4OdcXFd+5OXlnfIe0goVKigvL89gRCXb3Llz9be//c16GI6wCsR+OTk5Ov/884MeowcGgD+iSIXSbt26acSIEVq6dKnq1q0rKX+z6OPHj7t2Ez+Awmc1A7l69erAn8uUKVNimnNs3LhRjRs3Dnr9BTn1ukvqyo8zbRtQ3LcUQMkSFRWlffv2BSafli9fHtiiBgDOJMRX8GbFImL9+vX69ddfJUm1a9c225QbQPGwadMmNWjQ4HcfA/6M22+//ZQbzPvvZZ0+fbrBqEquhx9+WOPHj7ceRrGUkpKiiRMnavPmzSpfvrxiYmLUu3fvwL3UAHA6RTKUllRer1fp6elBXfQKNn4C8Of0799fw4YN+93HipvevXvrggsuUIMGDRQfH6/atWtbDwkoFAV7AxTkvz3ggw8+MBhV8ZeTk6PSpUsrOztbPp9PZcuWVUZGBlsgAfhdhNIi4osvvtCsWbNUsWLFwAdtSEiIRo4caTwyoOjasmWLNm/erHnz5gXdY5aVlaVVq1ZpxIgRhqNz3vHjx7V161Zt2rRJmzdvVnJysmJjY7kdAsCf0rdvX/Xs2TNwb+vy5cs1ffp0vfbaa8YjA3C242aWImLevHl69dVXFRUVZT0UoNjIzc1Vdna28vLydPTo0cDj5cqVU58+fQxH5o7Q0FCFh4crNDRUISEhqlChgipWrOhYvRM7qJ+IfZeBou3xxx/X+PHj1bBhQ/322286fPiwnnvuOethASgCCKVFRLVq1VzbZwwoKRo2bKiGDRuqXbt2io6O1rFjx1SmTBnrYbmmW7duio2N1fXXX6+OHTs6Punl777r8/mUmpqqyMhI+Xw+HTlyRNWqVSuxjZCA4iI2NlY333yzxowZo7Jly+qFF15Q1apVrYcFoAhg+e5Zbu7cuZKkX3/9VcnJyWrWrFnQlhXsbwf8dVu2bNH48eOVnZ2t8ePHa8eOHUpMTNSDDz5oPTRHrVq1Sps2bdK2bdsUHh6uCy+8UPHx8broooscrfuf//xHLVu2VLNmzSRJa9eu1apVq/TQQw85WheAs8aPH6+UlBQ98sgjSk5O1tSpU3XNNdfommuusR4agLMcm0ed5Y4ePaqjR4+qWrVqSkhIUG5ubuCxgssNAfx5U6dO1cCBAwNXCuvUqaOffvrJeFTOa9Gihe655x499NBDatq0qb755hsNHTrU8bpbt24NBFJJatq0qTZv3ux4XQDOio2N1aBBgxQTE6MmTZro5Zdf1i+//GI9LABFAMt3z3K33Xab9RCAEuHETtYlYcP3kSNHaufOnapRo4bi4+P16KOPnrTxvROqVKmijz76SJdddpkkacmSJapSpYrjdQE4q2DDOCn//vyHH37YaDQAihJCaRExePBg9enTR+XLl5eU3zDktdde08CBA41HBhR9VatW1ebNmxUSEqLc3FzNmzdP5557rvWwHLNt2zZVq1ZNN998s+rWratFixZpxYoVSk9PV2xsrEqXLu1o/ccff1wzZ87UyJEjFRISovj4eD3++OOO1gTgvH/84x+n3IpnzJgxBqMBUJQQSouIjIyMQCCV8rtUHjp0yHBEQPHRo0cPTZ06VQcPHlSvXr2UkJCgBx54wHpYjpk0aZKeffZZ1atXTxs3btT06dPVvXt37dixQxMmTFDfvn0drR8ZGanu3bsrOztbERERjtYC4J6Cy/+PHz+u77777ne7bgOARCgtMkJDQ5WamhpYYnjgwIFTzkYC+P+rUKGCHnvsMethuMbr9Qa2X1m2bJk6duyoSy65RJdccokre5Ru3rxZ//nPf0pcYymguDuxg/ff/vY39e/fX7fffrvRiAAUFYTSIuLOO+/Us88+q4YNG8rn82nTpk10qgT+olmzZp3x+S5durg0End5vV7l5eUpLCxM69evDzqWeL1ex+tPmzZNAwcO1PDhwyWVnMZSQHG3ffv2wJ99Pp9+/vlnV44pAIo+QmkR0aRJEw0bNkxbt26VJN13332qUKGC8aiAou1Ue5IeO3ZMX3/9tQ4fPlxsQ2mbNm30/PPPKyoqSqVLl1Z8fLwkad++fa7th1wSG0sBxd0777wT+HNoaKhiYmL05JNPGo4IQFFBKC0ifD6f1q1bp/3796tLly5KTU3Vtm3bXOmUCRRXN9xwQ+DPR48e1bx587Rw4UK1bt066Lni5pZbblHjxo2Vnp6uhISEwK0AXq9X3bt3d7x+SWssBZQUgwYNOumxzz//XDVr1jQYDYCiJMTn8/msB4HfN2nSJIWEhGjDhg0aPXq0MjMz9dJLL2nIkCHWQwOKtMzMTM2dO1eLFy/WFVdcoeuuuy5wvyWckZGRoalTp+rHH3+Uz+dTQkKC7r//fv7dgWLo4Ycf1vjx462HAeAsx5XSImLbtm0aNmyY+vXrJym/e2Vubq7xqICi7Z133tHKlSvVsWNHvfLKK3SCdUlycvJJjaU2bdqkBg0aGI0IAABYIpQWEWFhYfJ6vYFldhkZGXTfBf6iuXPnKjw8XLNnz9bHH38ceNzn8ykkJETTpk0zHF3xNWXKFA0bNux3HwMAACUDobSIuPbaazVixAgdOnRI06dP1/Lly3XHHXdYDwso0j788EPrIZQoW7Zs0ebNm5WRkaG5c+cGHs/KyqJDJ1CE3XvvvaecKPf5fMrJyTEYEYCihntKi5A9e/boxx9/lCQ1btxYtWrVMh4RAPxxGzdu1IYNG/TVV1/pyiuvDDxetmxZNW/eXOecc47h6AAAgBVCaRExfvx4XXvttapTp07gsRkzZqhr1652gwKAP+HAgQOKjo62HgYAADhLsHy3iPj++++1fft2XX/99briiiskSatXryaUAigypk6dqvvuu0+TJ08+5VK//v37G4wKAABYI5QWERUrVtSgQYP0+uuva+vWrerevbu4yA2gKLn88sslSZ07dzYeCQAAOJsQSosIn8+ncuXK6emnn9aMGTP0/PPPKysry3pYAPCHxcXFSZIaNmxoPBIAAHA2IZQWER6PJ/Dnrl27Ki4uTp9//rnhiADgz9m0aZNmzpyp1NRU5eXlBbbgGTNmjPXQAACAARodneX27dun9PT0kzaV37RpkypVqqQaNWoYjQwA/pwnnnhC3bp1U1xcnEJDQwOPR0VFGY4KAABYCf39/wWWpk6dqnLlyp30eLly5TR16lT3BwQAf1G5cuXUtGlTVaxYUVFRUYH/AABAycTy3bPcoUOHFBsbe9LjsbGxOnDggMGIAOCvadSokd555x21atVK4eH/+xjy33MKAABKFkLpWe7IkSOnfS4nJ8fFkQBA4di2bZskafv27UGPDxo0yGI4AADAGKH0LBcXF6fExER16tQp6PEFCxZwVQFAkUT4BAAABdHo6CyXnp6ukSNHKjw8PBBCf/75Z+Xm5uqpp55SpUqVbAcIAH/Q3LlzT3qsQoUKatCggWJiYgxGBAAAzgaE0iJi/fr1+vXXXyVJtWvXVuPGjY1HBAD/PzNnzjzpsczMTH3//fe67bbb1KZNG4NRAQAAa4RSAICpzMxMDR48WMOGDbMeCgAAMMCWMAAAU5GRkWJ+FACAkotQCgAwtX79epUvX956GAAAwAjddwEArujbt69CQkKCHsvMzFTlypX16KOPGo0KAABY455SAIArDhw4EPR1SEiIIiMjFRERYTQiAABwNiCUAgAAAADMcE8pAAAAAMAMoRQAAAAAYIZQCgAAAAAwQygFAAAAAJj5P7u6MvAYlkCiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.dropna()['country'].value_counts().plot(kind='bar', color='C0', logy=True, figsize=(16, 9));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How does that look like on the Map?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.dropna().plot(kind='scatter', x='city_lon', y='city_lat', figsize=(16, 9))\n",
    "plt.axis('equal');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.collections import LineCollection\n",
    "\n",
    "df_plot = df.dropna()\n",
    "lines = [[(lon0, lat0), (lon1, lat1)] \n",
    "         for lon0, lat0, lon1, lat1 in df_plot[['city_lon', \n",
    "                                                'city_lat', \n",
    "                                                'birth_city_lon', \n",
    "                                                'birth_city_lat']].values]\n",
    "\n",
    "line_collection = LineCollection(lines, linewidths=2)\n",
    "\n",
    "plt.figure(figsize=(16, 9))\n",
    "plt.gca().add_collection(line_collection)\n",
    "plt.gca().autoscale()\n",
    "plt.axis('equal');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# What is the Average Age of a Mayor?\n",
    "\n",
    "We can see that 55 years is the prime age to be a mayor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average age : 54.92 (+/- 9.75)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['age'].plot(kind='hist', bins=50, figsize=(16, 9));\n",
    "print('Average age : {:.2f} (+/- {:.2f})'.format(df['age'].mean(), df['age'].std()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['duration'].plot(kind='hist', bins=20, figsize=(16, 9));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>city</th>\n",
       "      <th>cityLabel</th>\n",
       "      <th>population</th>\n",
       "      <th>mayor</th>\n",
       "      <th>mayorLabel</th>\n",
       "      <th>genderLabel</th>\n",
       "      <th>birth</th>\n",
       "      <th>age</th>\n",
       "      <th>start_date</th>\n",
       "      <th>duration</th>\n",
       "      <th>birth_country</th>\n",
       "      <th>birth_countryLabel</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_cityLabel</th>\n",
       "      <th>city_lon</th>\n",
       "      <th>city_lat</th>\n",
       "      <th>birth_city_lon</th>\n",
       "      <th>birth_city_lat</th>\n",
       "      <th>distance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>593</th>\n",
       "      <td>Spain</td>\n",
       "      <td>http://www.wikidata.org/entity/Q10282</td>\n",
       "      <td>Pamplona</td>\n",
       "      <td>201653.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q2223568</td>\n",
       "      <td>Enrique Maya Miranda</td>\n",
       "      <td>male</td>\n",
       "      <td>1959-11-07</td>\n",
       "      <td>61.0</td>\n",
       "      <td>2019-06-15</td>\n",
       "      <td>1</td>\n",
       "      <td>http://www.wikidata.org/entity/Q77</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1335</td>\n",
       "      <td>Montevideo</td>\n",
       "      <td>-1.650000</td>\n",
       "      <td>42.816667</td>\n",
       "      <td>-56.166667</td>\n",
       "      <td>-34.866667</td>\n",
       "      <td>1.023175e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>710</th>\n",
       "      <td>France</td>\n",
       "      <td>http://www.wikidata.org/entity/Q249884</td>\n",
       "      <td>Saint-Pierre</td>\n",
       "      <td>84212.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q3309639</td>\n",
       "      <td>Michel Fontaine</td>\n",
       "      <td>male</td>\n",
       "      <td>1952-01-01</td>\n",
       "      <td>68.0</td>\n",
       "      <td>2001-01-01</td>\n",
       "      <td>19</td>\n",
       "      <td>http://www.wikidata.org/entity/Q142</td>\n",
       "      <td>France</td>\n",
       "      <td>http://www.wikidata.org/entity/Q239078</td>\n",
       "      <td>Romans-sur-Isère</td>\n",
       "      <td>55.477778</td>\n",
       "      <td>-21.341944</td>\n",
       "      <td>5.050833</td>\n",
       "      <td>45.045556</td>\n",
       "      <td>8.951750e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>730</th>\n",
       "      <td>France</td>\n",
       "      <td>http://www.wikidata.org/entity/Q249884</td>\n",
       "      <td>Saint-Pierre</td>\n",
       "      <td>84212.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q3309639</td>\n",
       "      <td>Michel Fontaine</td>\n",
       "      <td>male</td>\n",
       "      <td>1952-05-06</td>\n",
       "      <td>68.0</td>\n",
       "      <td>2001-01-01</td>\n",
       "      <td>19</td>\n",
       "      <td>http://www.wikidata.org/entity/Q142</td>\n",
       "      <td>France</td>\n",
       "      <td>http://www.wikidata.org/entity/Q239078</td>\n",
       "      <td>Romans-sur-Isère</td>\n",
       "      <td>55.477778</td>\n",
       "      <td>-21.341944</td>\n",
       "      <td>5.050833</td>\n",
       "      <td>45.045556</td>\n",
       "      <td>8.951750e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>566</th>\n",
       "      <td>Switzerland</td>\n",
       "      <td>http://www.wikidata.org/entity/Q72</td>\n",
       "      <td>Zürich</td>\n",
       "      <td>434008.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q123363</td>\n",
       "      <td>Corine Mauch</td>\n",
       "      <td>female</td>\n",
       "      <td>1960-05-28</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2009-05-01</td>\n",
       "      <td>11</td>\n",
       "      <td>http://www.wikidata.org/entity/Q30</td>\n",
       "      <td>United States of America</td>\n",
       "      <td>http://www.wikidata.org/entity/Q487977</td>\n",
       "      <td>Iowa City</td>\n",
       "      <td>8.540000</td>\n",
       "      <td>47.378611</td>\n",
       "      <td>-91.525000</td>\n",
       "      <td>41.655833</td>\n",
       "      <td>7.401167e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>776</th>\n",
       "      <td>Denmark</td>\n",
       "      <td>http://www.wikidata.org/entity/Q21176</td>\n",
       "      <td>Viborg</td>\n",
       "      <td>40371.0</td>\n",
       "      <td>http://www.wikidata.org/entity/Q1364114</td>\n",
       "      <td>Ulrik Wilbek</td>\n",
       "      <td>male</td>\n",
       "      <td>1958-04-13</td>\n",
       "      <td>62.0</td>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>2</td>\n",
       "      <td>http://www.wikidata.org/entity/Q948</td>\n",
       "      <td>Tunisia</td>\n",
       "      <td>http://www.wikidata.org/entity/Q3572</td>\n",
       "      <td>Tunis</td>\n",
       "      <td>9.400000</td>\n",
       "      <td>56.450000</td>\n",
       "      <td>10.180000</td>\n",
       "      <td>36.800833</td>\n",
       "      <td>2.185042e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         country                                    city     cityLabel  \\\n",
       "593        Spain   http://www.wikidata.org/entity/Q10282      Pamplona   \n",
       "710       France  http://www.wikidata.org/entity/Q249884  Saint-Pierre   \n",
       "730       France  http://www.wikidata.org/entity/Q249884  Saint-Pierre   \n",
       "566  Switzerland      http://www.wikidata.org/entity/Q72        Zürich   \n",
       "776      Denmark   http://www.wikidata.org/entity/Q21176        Viborg   \n",
       "\n",
       "     population                                    mayor  \\\n",
       "593    201653.0  http://www.wikidata.org/entity/Q2223568   \n",
       "710     84212.0  http://www.wikidata.org/entity/Q3309639   \n",
       "730     84212.0  http://www.wikidata.org/entity/Q3309639   \n",
       "566    434008.0   http://www.wikidata.org/entity/Q123363   \n",
       "776     40371.0  http://www.wikidata.org/entity/Q1364114   \n",
       "\n",
       "               mayorLabel genderLabel       birth   age  start_date  duration  \\\n",
       "593  Enrique Maya Miranda        male  1959-11-07  61.0  2019-06-15         1   \n",
       "710       Michel Fontaine        male  1952-01-01  68.0  2001-01-01        19   \n",
       "730       Michel Fontaine        male  1952-05-06  68.0  2001-01-01        19   \n",
       "566          Corine Mauch      female  1960-05-28  60.0  2009-05-01        11   \n",
       "776          Ulrik Wilbek        male  1958-04-13  62.0  2018-01-01         2   \n",
       "\n",
       "                           birth_country        birth_countryLabel  \\\n",
       "593   http://www.wikidata.org/entity/Q77                   Uruguay   \n",
       "710  http://www.wikidata.org/entity/Q142                    France   \n",
       "730  http://www.wikidata.org/entity/Q142                    France   \n",
       "566   http://www.wikidata.org/entity/Q30  United States of America   \n",
       "776  http://www.wikidata.org/entity/Q948                   Tunisia   \n",
       "\n",
       "                                 birth_city   birth_cityLabel   city_lon  \\\n",
       "593    http://www.wikidata.org/entity/Q1335        Montevideo  -1.650000   \n",
       "710  http://www.wikidata.org/entity/Q239078  Romans-sur-Isère  55.477778   \n",
       "730  http://www.wikidata.org/entity/Q239078  Romans-sur-Isère  55.477778   \n",
       "566  http://www.wikidata.org/entity/Q487977         Iowa City   8.540000   \n",
       "776    http://www.wikidata.org/entity/Q3572             Tunis   9.400000   \n",
       "\n",
       "      city_lat  birth_city_lon  birth_city_lat      distance  \n",
       "593  42.816667      -56.166667      -34.866667  1.023175e+07  \n",
       "710 -21.341944        5.050833       45.045556  8.951750e+06  \n",
       "730 -21.341944        5.050833       45.045556  8.951750e+06  \n",
       "566  47.378611      -91.525000       41.655833  7.401167e+06  \n",
       "776  56.450000       10.180000       36.800833  2.185042e+06  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by='distance', ascending=False).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.plotting import scatter_matrix\n",
    "\n",
    "df_plot = df[['age', 'duration', 'population', 'distance']].copy()\n",
    "for col in ['population', 'duration']:\n",
    "    df_plot[col] = df_plot[col].apply(lambda x: np.log(x) if x > 0 else 0)\n",
    "df_plot['distance'] = df_plot['distance'].apply(lambda x: np.log(x) if x > 0 else 0)\n",
    "scatter_matrix(df_plot, alpha=0.5, figsize=(10, 10), diagonal='kde');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conclusion\n",
    "\n",
    "We have learned how to work with Wikidata and SPARQL and also how to integrate it with Python and Pandas.  Wikidata is a great database that enables queries and discoveries that would not be possible with ordinary searches on your favorite search engine. This opens up exciting new possibilities to do data science and exploratory data analysis and a fascinating new way to learn about relationships and curious findings in our accumulated human knowledge.\n",
    "\n",
    "## Resources and a Pile of Links\n",
    "\n",
    "A good read covering the history and an overview of Wikidata can be found in the article [Wikidata: a free collaborative knowledge base.](http://delivery.acm.org/10.1145/2630000/2629489/p78-vrandecic.pdf?ip=188.23.116.132&id=2629489&acc=OA&key=4D4702B0C3E38B35%2E4D4702B0C3E38B35%2E4D4702B0C3E38B35%2EB8CD93A2515AABD1&__acm__=1533116941_da1ef0b41c8a6ea97e62187e7e72de90) by Vrandečić, D., & Krötzsch, M. (2014). There is a great [SPARQL tutorial](https://www.wikidata.org/wiki/Wikidata:SPARQL_tutorial) covering many of the things mentioned here and goes into much more depth into understanding SPARQL. If you are excited about Wikidata and want to contribute, there are [Wikidata Tours](https://www.wikidata.org/wiki/Wikidata:Tours) that can guide you through the process. If you plan on doing large queries, make sure to take a look at the publicly downloadable [Wikidata dumps](https://dumps.wikimedia.org/wikidatawiki/entities/) which are regularly updated dumps of the whole Wikidata data set and here is a documentation on the [Wikibase data model](https://www.mediawiki.org/wiki/Wikibase/DataModel). Wikidata provides also a list of [Tools for programmers](https://www.wikidata.org/wiki/Wikidata:Tools/For_programmers).\n",
    "\n",
    "Here is an unstructured list of resources that contain useful documentation, tutorials or examples that use Wikidata.\n",
    "\n",
    "- [RDF Exports from Wikidata](https://tools.wmflabs.org/wikidata-exports/rdf/)\n",
    "- [Wikidata:List of properties](https://www.wikidata.org/wiki/Wikidata:List_of_properties)\n",
    "- [Wikidata:Database reports](https://www.wikidata.org/wiki/Wikidata:Database_reports)\n",
    "- [Wikidata:Database reports/List of properties/Top100](https://www.wikidata.org/wiki/Wikidata:Database_reports/List_of_properties/Top100)\n",
    "- [Wikidata:Introduction](https://www.wikidata.org/wiki/Wikidata:Introduction)\n",
    "- [Wikidata:SPARQL queries](https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/queries)\n",
    "- [Wikidata:SPARQL queries examples](https://www.wikidata.org/wiki/Wikidata:SPARQL_query_service/queries/examples)\n",
    "- [Wikidata:Creating a bot](https://www.wikidata.org/wiki/Wikidata:Creating_a_bot)\n",
    "- [Querying Wikidata About Vienna’s Tram Lines: An Introduction to SPARQL](https://noniq.at/0016/wikidata-sparql-introduction/)\n",
    "- [How US Presidents Died According to Wikidata](http://ramiro.org/notebook/us-presidents-causes-of-death/)\n",
    "- [An Ambitious Wikidata Tutorial - SlideShare](https://de.slideshare.net/_Emw/an-ambitious-wikidata-tutorial)\n",
    "- [Wikidata Graph Builder](https://angryloki.github.io/wikidata-graph-builder/), great tool to visualize Wikidata graphs\n",
    "- [Histropedia](http://histropedia.com), visualization of historical timelines"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[List of available SPARQL endpoints](https://www.w3.org/wiki/SparqlEndpoints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}